Scholars@Duke
Leslie M. Collins

Leslie M. Collins

Professor of Electrical and Computer Engineering
Pierre R. Lamond Department of Electrical and Computer Engineering
lcollins@ee.duke.edu
Box 90291, Durham, NC 27708-0291
3461 CIEMAS, Durham, NC 27708

Scholarly Works - Conferences

A Data-Centric Analysis of the Impact of Training Data Quality vs. Quantity on P300 Brain-Computer Interface Performance (Student Abstract)

Conference Proceedings of the Aaai Conference on Artificial Intelligence · January 1, 2026 The current standard for training brain-computer interface (BCI) machine learning models is user-specific. There is a high interest in developing generic models that are trained on data from other users to minimize BCI calibration time; however, this is li ... Full text Cite

Assessing the Impact of Population Data Domain Differences on Transfer Learning in P300-based Brain-Computer Interfaces

Conference Proceedings of the Aaai Conference on Artificial Intelligence · April 11, 2025 Brain-computer interfaces (BCIs) can provide a means of communication for individuals with severe neuromuscular diseases, the target end-users. While personalized BCI machine learning models are the current standard, models trained on data from other users ... Full text Cite

Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer

Conference Proceedings 2025 IEEE Winter Conference on Applications of Computer Vision Wacv 2025 · January 1, 2025 Recent object detection models for infrared (IR) imagery are based upon deep neural networks (DNNs) and require large amounts of labeled training imagery. However, publicly available datasets that can be used for such training are limited in their size and ... Full text Cite

SIMPL Multi-Aspect MADD: Rapidly Generating Low-Cost Multi-Aspect Military Data for All-Domains at Scale

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2025 In this work we extend an approach known as SIMPL (Synthetic object IMPLantation) to construct a large and diverse synthetic dataset known as MADD (Military All-Domain Dataset). Our extension to SIMPL provides the ability to easily and rapidly generate a m ... Full text Cite

Segment anything, from space?

Conference Proceedings 2024 IEEE Winter Conference on Applications of Computer Vision Wacv 2024 · January 3, 2024 Recently, the first foundation model developed specifically for image segmentation tasks was developed, termed the "Segment Anything Model"(SAM). SAM can segment objects in input imagery based on cheap input prompts, such as one (or more) points, a boundin ... Full text Cite

Mixture Manifold Networks: A Computationally Efficient Baseline for Inverse Modeling

Conference Proceedings of the 37th Aaai Conference on Artificial Intelligence Aaai 2023 · June 27, 2023 We propose and show the efficacy of a new method to address generic inverse problems. Inverse modeling is the task whereby one seeks to determine the control parameters of a natural system that produce a given set of observed measurements. Recent work has ... Full text Cite

Transformers For Recognition In Overhead Imagery: A Reality Check

Conference Proceedings 2023 IEEE Winter Conference on Applications of Computer Vision Wacv 2023 · January 1, 2023 There is evidence that transformers offer state-of-the-art recognition performance on tasks involving overhead imagery (e.g., satellite imagery). However, it is difficult to make unbiased empirical comparisons between competing deep learning models, making ... Full text Cite

Suppressing reverberation in cochlear implant stimulus patterns using time-frequency masks based on phoneme groups

Conference Proceedings of Meetings on Acoustics · December 5, 2022 Cochlear implant (CI) users experience considerable difficulty in understanding speech in reverberant listening environments. This issue is commonly addressed with time-frequency masking, where a time-frequency decomposed reverberant signal is multiplied b ... Full text Cite

Language Model-Guided Classifier Adaptation for Brain-Computer Interfaces for Communication.

Conference Conference proceedings. IEEE International Conference on Systems, Man, and Cybernetics · October 2022 Brain-computer interfaces (BCIs), such as the P300 speller, can provide a means of communication for individuals with severe neuromuscular limitations. BCIs interpret electroencephalography (EEG) signals in order to translate embedded information about a u ... Full text Cite

Mitigating the Impact of Psychophysical Effects During Adaptive Stimulus Selection in the P300 Speller Brain-Computer Interface.

Conference Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · November 2021 Stimulus-driven brain-computer interfaces (BCIs), such as the P300 speller, rely on using sensory stimuli to elicit specific neural signal components called event-related potentials (ERPs) to control external devices. However, psychophysical factors, such ... Full text Cite

A causal deep learning framework for classifying phonemes in cochlear implants

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2021 Speech intelligibility in cochlear implant (CI) users degrades considerably in listening environments with reverberation and noise. Previous research in automatic speech recognition (ASR) has shown that phoneme-based speech enhancement algorithms improve A ... Full text Cite

Evaluating the effect of longitudinal dose and INR data on maintenance warfarin dose predictions

Conference Bhi 2021 2021 IEEE EMBS International Conference on Biomedical and Health Informatics Proceedings · January 1, 2021 Warfarin, a commonly prescribed drug to prevent blood clots, has a highly variable individual response. Determining a maintenance warfarin dose that achieves a therapeutic blood clotting time, as measured by the international normalized ratio (INR), is cru ... Full text Cite

APPLICATION OF COMPOSITIONAL NEURAL NETWORKS FOR ROBUST CLASSIFICATION OF INFRARED IMAGERY

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2021 Thermal infrared (IR) imaging has increasingly been used for remote sensing applications, which has required the adaptation of processing techniques for “natural images” (e.g., RGB images) to this unique domain in order to accommodate such differences as t ... Full text Cite

Do Deep Learning Models Generalize to Overhead Imagery from Novel Geographic Domains? the xGD Benchmark Problem

Conference International Geoscience and Remote Sensing Symposium IGARSS · September 26, 2020 Recently, Convolutional Neural Networks (CNNs) have demonstrated impressive performance on several visual recognition benchmark datasets utilizing overhead imagery. However, most of these analyses performed on benchmark datasets involve testing pre-trained ... Full text Cite

Mapping Electric Transmission Line Infrastructure from Aerial Imagery with Deep Learning

Conference International Geoscience and Remote Sensing Symposium IGARSS · September 26, 2020 Access to electricity positively correlates with many beneficial socioeconomic outcomes in the developing world including improvements in education, health, and poverty. Efficient planning for electricity access requires information on the location of exis ... Full text Cite

Heart Sound Analysis in Individuals Supported with Left Ventricular Assist Device: A First Look

Conference Computing in Cardiology · September 13, 2020 The left ventricular assist device (LVAD) has emerged as a bridge or alternative to heart transplant in individuals with advanced heart failure. However, the LVAD recipient population currently faces high rehospitalization rates. Remote analysis of precord ... Full text Cite

USING AUTOMATIC SPEECH RECOGNITION AND SPEECH SYNTHESIS TO IMPROVE THE INTELLIGIBILITY OF COCHLEAR IMPLANT USERS IN REVERBERANT LISTENING ENVIRONMENTS.

Conference Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · May 2020 Cochlear implant (CI) users experience substantial difficulties in understanding reverberant speech. A previous study proposed a strategy that leverages automatic speech recognition (ASR) to recognize reverberant speech and speech synthesis to translate th ... Full text Cite

How robust are deep object detectors to variability in ground truth bounding boxes? experiments for target recognition in infrared imagery

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2020 In this work we consider the problem of developing deep learning models - such as convolutional neural networks (CNNs) - for automatic target detection (ATD) in infrared (IR) imagery. CNN-based ATD systems must be trained to recognize objects using boundin ... Full text Cite

Training a single multi-class convolutional segmentation network using multiple datasets with heterogeneous labels: Preliminary results

Conference International Geoscience and Remote Sensing Symposium IGARSS · July 1, 2019 Segmentation convolutional neural networks (CNNs) are now popular for the semantic segmentation (i.e., dense pixel-wise labeling) of remote sensing imagery, such as color or hyperspectral satellite imagery. In recent years a large number of hand-labeled da ... Full text Cite

A simple rotational equivariance loss for generic convolutional segmentation networks: Preliminary results

Conference International Geoscience and Remote Sensing Symposium IGARSS · July 1, 2019 Segmentation convolutional neural networks (SCNNs) are now popular for the semantic segmentation (i.e., dense pixel-wise labeling) of remote sensing imagery, such as color or hyperspectral satellite imagery. One desirable property of SCNNs when applied to ... Full text Cite

Automated feature learning using deep convolutional auto-encoder neural network for clustering electroencephalograms into sleep stages

Conference International IEEE EMBS Conference on Neural Engineering Ner · May 16, 2019 Deep neural networks have emerged as popular machine learning tools due to their ability to automatically learn feature representations from raw input data. An auto-encoder neural network is a special network that can be trained in an unsupervised manner f ... Full text Cite

An exploration of gradient-based features for buried threat detection using a handheld ground penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2019 In this work we consider the problem of developing algorithms for the automatic detection of buried threats in handheld Ground Penetrating Radar (HH-GPR) data. The development of algorithms for HH-GPR is relatively nascent compared to larger downward-looki ... Full text Cite

How transferable are downward-looking and handheld ground penetrating radar data? Experiments in the context of buried threat detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2019 In this work we consider the problem of developing algorithms for the automatic detection of buried threats using handheld Ground Penetrating Radar (HH-GPR) data. The development of algorithms for HH-GPR is relatively nascent compared to algorithm developm ... Full text Cite

Reliable training of convolutional neural networks for GPR-based buried threat detection using the Adam optimizer and batch normalization

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2019 The ground penetrating radar (GPR) is a remote sensing technology that has been successfully used for detecting buried explosive threats. A large body of published research has focused on developing algorithms that automatically detect buried threats using ... Full text Cite

Data augmentation in feature-space with generative adversarial networks, applied to GPR-based buried threat detection

Conference 10th International Workshop on Advanced Ground Penetrating Radar Held at Near Surface Geoscience Conference and Exhibition 2019 Nsg 2019 · January 1, 2019 In this work we consider the problem of developing algorithms for automatic buried threat detection (BTD) in ground penetrating radar (GPR) data. Many such algorithms are supervised, and perform best when they can be trained on large quantities of labeled ... Cite

Application of a Graphical Model to Investigate the Utility of Cross-channel Information for Mitigating Reverberation in Cochlear Implants.

Conference Proceedings of the ... International Conference on Machine Learning and Applications. International Conference on Machine Learning and Applications · December 2018 Individuals with cochlear implants (CIs) experience more difficulty understanding speech in reverberant environ-ments than normal hearing listeners. As a result, recent research has targeted mitigating the effects of late reverberant signal reflections in ... Full text Cite

Large-scale semantic classification: Outcome of the first year of inria aerial image labeling benchmark

Conference International Geoscience and Remote Sensing Symposium IGARSS · October 31, 2018 Over the recent years, there has been an increasing interest in large-scale classification of remote sensing images. In this context, the Inria Aerial Image Labeling Benchmark has been released online in December 2016. In this paper, we discuss the outcome ... Full text Cite

On the extraction of training imagery from very large remote sensing datasets for deep convolutional segmenatation networks

Conference International Geoscience and Remote Sensing Symposium IGARSS · October 31, 2018 In this work, we investigate strategies for training convolutional neural networks (CNNs) to perform recognition on remote sensing imagery. In particular we consider the particular problem of semantic segmentation in which the goal is to obtain a dense pix ... Full text Cite

Deep convolutional segmentation of remote sensing imagery: A simple and efficient alternative to stitching output labels

Conference International Geoscience and Remote Sensing Symposium IGARSS · October 31, 2018 In this work we consider the application of convolutional neural networks (CNNs) for the semantic segmentation of remote sensing imagery (e.g., aerial color or hyperspectral imagery). In segmentation the goal is to provide a dense pixel-wise labeling of th ... Full text Cite

Semisupervised adversarial discriminative domain adaptation, with application to remote sensing data

Conference International Geoscience and Remote Sensing Symposium IGARSS · October 31, 2018 Recently, convolutional neural networks (CNNs) have received substantial attention in the literature for object recognition (e.g., buildings and roads) in several remote sensing data modalities (e.g., aerial color imagery). Although CNNs have exhibited exc ... Full text Cite

Augmented Latent Dirichlet Allocation (Lda) Topic Model with Gaussian Mixture Topics

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · September 10, 2018 Latent Dirichlet allocation (LDA) is a statistical model that is often used to discover topics or themes in a large collection of documents. In the LDA model, topics are modeled as discrete distributions over a finite vocabulary of words. The LDA is also a ... Full text Cite

Neurophysiology of Visual-Motor Learning during a Simulated Marksmanship Task in Immersive Virtual Reality

Conference 25th IEEE Conference on Virtual Reality and 3D User Interfaces VR 2018 Proceedings · August 24, 2018 Immersive virtual reality (VR) systems offer flexible control of an interactive environment, along with precise position and orientation tracking of realistic movements. Immersive VR can also be used in conjunction with neurophysiological monitoring techni ... Full text Open Access Cite

USING MACHINE LEARNING TO MITIGATE THE EFFECTS OF REVERBERATION AND NOISE IN COCHLEAR IMPLANTS.

Conference Proceedings of meetings on acoustics. Acoustical Society of America · May 2018 In listening environments with room reverberation and background noise, cochlear implant (CI) users experience substantial difficulties in understanding speech. Because everyday environments have different combinations of reverberation and noise, there is ... Full text Cite

If training data appears to be mislabeled, should we relabel it? Improving supervised learning algorithms for threat detection in ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2018 This work focuses on the development of automatic buried threat detection (BTD) algorithms using ground penetrating radar (GPR) data. Buried threats tend to exhibit unique characteristics in GPR imagery, such as high energy hyperbolic shapes, which can be ... Full text Cite

How do we choose the best model? The impact of cross-validation design on model evaluation for buried threat detection in ground penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2018 A great deal of research has been focused on the development of computer algorithms for buried threat detection (BTD) in ground penetrating radar (GPR) data. Most recently proposed BTD algorithms are supervised, and therefore they employ machine learning m ... Full text Cite

Improving the histogram of oriented gradient feature for threat detection in ground penetrating radar by implementing it as a trainable convolutional neural network

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2018 A large number of algorithms have been proposed for automatic buried threat detection (BTD) in ground penetrating radar (GPR) data. Convolutional neural networks (CNNs) have recently achieved groundbreaking results on many recognition tasks. This success i ... Full text Cite

How much shape information is enough, or too much? Designing imaging descriptors for threat detection in ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2018 In this work, we consider the development of algorithms for automated buried threat detection (BTD) using Ground Penetrating Radar (GPR) data. When viewed in GPR imagery, buried threats often exhibit hyperbolic shapes, and this characteristic shape can be ... Full text Cite

Information-based adaptive stimulus selection to optimize communication efficiency in brain-computer interfaces

Conference Advances in Neural Information Processing Systems · January 1, 2018 Stimulus-driven brain-computer interfaces (BCIs), such as the P300 speller, rely on using a sequence of sensory stimuli to elicit specific neural responses as control signals, while a user attends to relevant target stimuli that occur within the sequence. ... Cite

Non-intrusive load monitoring system performance over a range of low frequency sampling rates

Conference 2017 6th International Conference on Renewable Energy Research and Applications Icrera 2017 · December 12, 2017 Non-intrusive load monitoring (NILM) systems estimate the amount of energy each appliance consumes using as input the aggregate building energy consumption. Typically, NILM results are presented for a single sampling rate. To evaluate tradeoffs between end ... Full text Cite

Estimating the electricity generation capacity of solar photovoltaic arrays using only color aerial imagery

Conference International Geoscience and Remote Sensing Symposium IGARSS · December 1, 2017 In this work, the problem of developing algorithms that automatically infer information about small-scale solar photovoltaic (PV) arrays in high resolution aerial imagery is considered. Such algorithms potentially offer a faster and cheaper solution to col ... Full text Cite

Trading spatial resolution for improved accuracy when using detection algorithms on remote sensing imagery

Conference International Geoscience and Remote Sensing Symposium IGARSS · December 1, 2017 In this work, we consider the problem of detecting target objects in remote sensing imagery; such as detecting rooftops, trees, or cars in color/hyperspectral imagery. Many detection algorithms for this problem work by assigning a decision statistic (or 'c ... Full text Cite

A deep convolutional neural network, with pre-training, for solar photovoltaic array detection in aerial imagery

Conference International Geoscience and Remote Sensing Symposium IGARSS · December 1, 2017 In this work we consider the problem of developing algorithms that automatically identify small-scale solar photovoltaic arrays in high resolution aerial imagery. Such algorithms potentially offer a faster and cheaper solution to collecting small-scale pho ... Full text Cite

Adaptive stimulus selection in ERP-based brain-computer interfaces by maximizing expected discrimination gain

Conference 2017 IEEE International Conference on Systems Man and Cybernetics Smc 2017 · November 27, 2017 Brain-computer interfaces (BCIs) can provide an alternative means of communication for individuals with severe neuromuscular limitations. The P300-based BCI speller relies on eliciting and detecting transient event-related potentials (ERPs) in electroencep ... Full text Cite

Three-dimensional features, based on beamforming at multiple depths, improves landmine detection with a forward-looking ground-penetrating radar

Conference 2017 9th International Workshop on Advanced Ground Penetrating Radar Iwagpr 2017 Proceedings · July 28, 2017 Forward-looking ground-penetrating radar (FLGPR) has been investigated as a remote sensing modality for buried threat detection (e.g., landmines). Generally in this context, raw FLGPR data is beamformed into two-dimensional images and then automated algori ... Full text Cite

Some good practices for applying convolutional neural networks to buried threat detection in Ground Penetrating Radar

Conference 2017 9th International Workshop on Advanced Ground Penetrating Radar Iwagpr 2017 Proceedings · July 28, 2017 Ground Penetrating Radar (GPR) is a remote sensing modality that has been researched extensively for buried threat detection. For this purpose, algorithms can be developed to automatically determine the presence of such threats. To train such algorithms, s ... Full text Cite

The effect of translational variance in training and testing images on supervised buried threat detection algorithms for ground penetrating radar

Conference 2017 9th International Workshop on Advanced Ground Penetrating Radar Iwagpr 2017 Proceedings · July 28, 2017 A large body of recent research has focused on the development of supervised buried threat detection algorithms for ground penetrating radar (GPR) data. Such algorithms learn to automatically identify landmines in GPR data based on threat data and non-thre ... Full text Cite

Trading spatial resolution for improved accuracy in remote sensing imagery: An empirical study using synthetic data

Conference Proceedings Applied Imagery Pattern Recognition Workshop · July 2, 2017 We consider the problem of detecting objects (such as trees, rooftops, roads, or cars) in remote sensing data including, for example, color or hyperspectral imagery. Many detection algorithms applied to this problem operate by assigning a decision statisti ... Full text Cite

The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: An empirical study with solar array detection

Conference Proceedings Applied Imagery Pattern Recognition Workshop · July 2, 2017 Convolutional neural networks (CNNs) have recently achieved unprecedented performance for the automatic recognition of objects (e.g., buildings, roads, or vehicles) in color aerial imagery. Although these results are promising, questions remain about their ... Full text Cite

The poor generalization of deep convolutional networks to aerial imagery from new geographic locations: An empirical study with solar array detection

Conference Proceedings Applied Imagery Pattern Recognition Workshop · July 2, 2017 Convolutional neural networks (CNNs) have recently achieved unprecedented performance for the automatic recognition of objects (e.g., buildings, roads, or vehicles) in color aerial imagery. Although these results are promising, questions remain about their ... Full text Cite

A performance-based approach to designing the stimulus presentation paradigm for the P300-based BCI by exploiting coding theory

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · June 16, 2017 The P300-based brain-computer interface (BCI) speller relies on eliciting and detecting specific brain responses to target stimulus events, termed event-related potentials (ERPs). In a visual speller, ERPs are elicited when the user's desired character, i. ... Full text Cite

An improved frequency domain feature with partial least-squares dimensionality reduction for classifying buried threats in forwardlooking ground-penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2017 Forward-looking ground penetrating radar (FLGPR) is a remote sensing modality that has been investigated for buried threat detection. The FLGPR considered in this work consists of a sensor array mounted on the front of a vehicle, which inspects an area in ... Full text Cite

Improvements to the histogram of oriented gradient (HOG) prescreener for buried threat detection in ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2017 Ground penetrating radar (GPR) systems have emerged as a state-of-the-art remote sensing platform for the automatic detection of buried explosive threats. The GPR system that was used to collect the data considered in this work consists of an array of rada ... Full text Cite

Discriminative dictionary learning to learn effective features for detecting buried threats in ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2017 The ground penetrating radar (GPR) is a popular remote sensing modality for buried threat detection. In this work we focus on the development of supervised machine learning algorithms that automatically identify buried threats in GPR data. An important ste ... Full text Cite

Learning improved pooling regions for the histogram of oriented gradient (HOG) feature for buried threat detection in ground penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2017 In recent years, the Ground Penetrating Radar (GPR) has successfully been applied to the problem of buried threat detection (BTD). A large body of research has focused on using computerized algorithms to automatically discriminate between buried threats an ... Full text Cite

Improving convolutional neural networks for buried target detection in ground penetrating radar using transfer learning via pre-training

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2017 The Ground Penetrating Radar (GPR) is a remote sensing modality that has been used to collect data for the task of buried threat detection. The returns of the GPR can be organized as images in which the characteristic visual patterns of threats can be leve ... Full text Cite

Sensor fusion for buried explosive threat detection for handheld data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2017 Data from multiple sensors has been collected using a handheld system, and includes precise location information. These sensors include ground penetrating radar (GPR) and electromagnetic induction (EMI) sensors. The performance of these sensors on differen ... Full text Cite

Leveraging seed dictionaries to improve dictionary learning

Conference Proceedings International Conference on Image Processing Icip · August 3, 2016 Most state-of-the-art dictionary learning algorithms (DLAs) are iterative, and must begin with an initial estimate of the dictionary, referred to as the seed. A seed can be generated randomly, but it has been shown that choosing a more intelligent seed oft ... Full text Cite

Performance comparison framework for energy disaggregation systems

Conference 2015 IEEE International Conference on Smart Grid Communications Smartgridcomm 2015 · March 17, 2016 Energy disaggregation algorithms decompose building-level energy data into device-level information. We conduct a head-To-head comparison of energy disaggregation techniques across multiple metrics and data sets. Our framework for analyzing the performance ... Full text Cite

A feature learning approach for classifying buried threats in forward looking ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2016 The forward-looking ground penetrating radar (FLGPR) is a remote sensing modality that has recently been investigated for buried threat detection. The FLGPR considered in this work uses stepped frequency sensing followed by filtered backprojection to creat ... Full text Cite

Attribute-driven transfer learning for detecting novel buried threats with ground-penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2016 Ground-penetrating radar (GPR) technology is an effective method of detecting buried explosive threats. The system uses a binary classifier to distinguish "targets", or buried threats, from "nontargets" arising from system prescreener false alarms; this cl ... Full text Cite

Algorithm development for deeply buried threat detection in GPR data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2016 Ground penetrating radar (GPR) is a popular remote sensing modality for buried threat detection. Many algorithms have been developed to detect buried threats using GPR data. One on-going challenge with GPR is the detection of very deeply buried targets. In ... Full text Cite

Using queuing models to aid design and guide research effort for multimodality buried target detection systems

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2016 Many remote sensing modalities have been developed for buried target detection (BTD), each one offering relative advantages over the others. There has been interest in combining several modalities into a single BTD system that benefits from the advantages ... Full text Cite

Radiogenomics of glioblastoma: A pilot multi-institutional study to investigate a relationship between tumor shape features and tumor molecular subtype

Conference Progress in Biomedical Optics and Imaging Proceedings of SPIE · January 1, 2016 Genomic subtype has been shown to be an important predictor of therapy response for patients with glioblastomas. Unfortunately, obtaining the genomic subtype is an expensive process that is not typically included in the standard of care. It is therefore of ... Full text Cite

Predicting outcomes in glioblastoma patients using computerized analysis of tumor shape - Preliminary data

Conference Progress in Biomedical Optics and Imaging Proceedings of SPIE · January 1, 2016 Glioblastoma (GBM) is the most common primary brain tumor characterized by very poor survival. However, while some patients survive only a few months, some might live for multiple years. Accurate prognosis of survival and stratification of patients allows ... Full text Cite

A deep convolutional neural network and a random forest classifier for solar photovoltaic array detection in aerial imagery

Conference 2016 IEEE International Conference on Renewable Energy Research and Applications Icrera 2016 · January 1, 2016 Power generation from distributed solar photovoltaic PV arrays has grown rapidly in recent years. As a result, there is interest in collecting information about the quantity, power capacity, and energy generated by such arrays; and to do so over small geo- ... Full text Cite

Image features for pixel-wise detection of solar photovoltaic arrays in aerial imagery using a random forest classifier

Conference 2016 IEEE International Conference on Renewable Energy Research and Applications Icrera 2016 · January 1, 2016 Power generation from distributed solar photovoltaic (PV) arrays has grown rapidly in recent years. As a result, there is interest in collecting information about the quantity, power capacity, and energy generated by such arrays; and to do so over small ge ... Full text Cite

Clutter and target discrimination in forward-looking ground penetrating radar using sparse structured basis pursuits

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2015 Forward-looking ground penetrating radar (FLGPR) is a remote sensing modality that has recently been investigated for buried threat detection. FLGPR offers greater standoff than other downward-looking modalities such as electromagnetic induction and downwa ... Full text Cite

Target signature localization in GPR data by jointly estimating and matching templates

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2015 Buried threat detection algorithms in Ground Penetrating Radar (GPR) measurements often utilize a statistical classifier to model target responses. There are many different target types with distinct responses and all are buried in a wide range of conditio ... Full text Cite

Leveraging robust principal component analysis to detect buried explosive threats in handheld ground-penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2015 A goal of ground penetrating radar (GPR) preprocessing is to distinguish background from data containing explosive threats. This is commonly achieved by performing depth-dependent mean and standard deviation normalization, where the mean and standard devia ... Full text Cite

A queuing model for designing multi-modality buried target detection systems: Preliminary results

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2015 Many remote sensing modalities have been developed for buried target detection, each one offering its own relative advantages over the others. As a result there has been interest in combining several modalities into a single detection platform that benefit ... Full text Cite

Recognizing subsurface target responses in ground penetrating radar data using convolutional neural networks

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2015 Improved performance in the discrimination of buried threats using Ground Penetrating Radar (GPR) data has recently been achieved using features developed for applications in computer vision. These features, designed to characterize local shape information ... Full text Cite

Improving buried threat detection in ground-penetrating radar with transfer learning and metadata analysis

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2015 Ground-penetrating radar (GPR) technology has proven capable of detecting buried threats. The system relies on a binary classifier that is trained to distinguish between two classes: a target class, encompassing many types of buried threats and their compo ... Full text Cite

Automatic solar photovoltaic panel detection in satellite imagery

Conference 2015 International Conference on Renewable Energy Research and Applications Icrera 2015 · January 1, 2015 The quantity of rooftop solar photovoltaic (PV) installations has grown rapidly in the US in recent years. There is a strong interest among decision makers in obtaining high quality information about rooftop PV, such as the locations, power capacity, and e ... Full text Cite

Physics-based deformations of ground penetrating radar signals to improve the detection of buried explosives

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 A number of recent algorithms have shown improved performance in detecting buried explosive threats by statistically modeling target responses observed in ground penetrating radar (GPR) signals. These methods extract features from known examples of target ... Full text Cite

Target localization and signature extraction in GPR data using expectation-maximization and principal component analysis

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 Ground Penetrating Radar (GPR) is a very promising technology for subsurface threat detection. A successful algorithm employing GPR should achieve high detection rates at a low false-alarm rate and do so at operationally relevant speeds. GPRs measure refle ... Full text Cite

A novel algorithm for buried target detection evaluated on a collection of seismo-acoustic data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 A recently validated technique for buried target detection relies on applying an acoustic stimulus signal to a patch of earth and then measuring its seismic (vibrational) response using a laser Doppler vibrometer (LDV). Target detection in this modality of ... Full text Cite

Hyperbolic and PLSDA filter algorithms to detect buried threats in GPR data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 Ground Penetrating radar (GPR) is a commonly used modality for the detection of buried threats. This work explores two approaches for buried threat detection in GPR data that we refer to as the hyperbolic filter and PLSDA filter algorithms. The hyperbolic ... Full text Cite

A robust Bayesian approach to target detection applied to explosive threat detection in handheld ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 Target detection algorithms for ground penetrating radar (GPR) data typically calculate local statistics for the background data surrounding a test sample as a means to assess changes in the data from background. To ensure that the local statistics are ind ... Full text Cite

Experiment design for measuring the probability of detection in remote sensing: How many objects and how many passes

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 Buried threat detection system (e.g., GPR, FLIR, EMI) performance can be summarized through two related statistics: the probability of detection (PD), and the false alarm rate (FAR). These statistics impact system rate of forward advance, clearance probabi ... Full text Cite

Fusion of forward looking infrared and ground penetrating radar for improved stopping distances in landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 Ground penetrating radar (GPR) is a popular sensing modality for buried threat detection that offers low false alarm rates (FARs), but suffers from a short detection stopping or standoff distance. This short stopping distance leaves little time for the sys ... Full text Cite

Target detection and identification using synthetic aperture acoustics

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2014 Recent research has shown that synthetic aperture acoustic (SAA) imaging may be useful for object identification. The goal of this work is to use SAA information to detect and identify four types of objects: jagged rocks, river rocks, small concave capped ... Full text Cite

A new approach to elemental inference in LIBS: A statistical model for spectral analysis

Conference Optics InfoBase Conference Papers · January 1, 2013 A new technique for automatic detection of elements in LIBS spectra is presented. The proposed model automatically determines the number of elements present in the spectra, and mitigates variations from unknown changes in plasma temperature. © OSA 2013. ... Cite

Rapid tracking for autonomous driving with monocular video

Conference 2013 International Conference on Connected Vehicles and Expo Iccve 2013 Proceedings · January 1, 2013 We present a novel tracking algorithm for an autonomous vehicle equipped with a single camera. Given only monocular visual data, our algorithm utilizes projective geometry to compute concise features of the environment. Using these features, road markings ... Full text Cite

A new approach to elemental inference in LIBS: A statistical model for spectral analysis

Conference Optics Infobase Conference Papers · January 1, 2013 A new technique for automatic detection of elements in LIBS spectra is presented. The proposed model automatically determines the number of elements present in the spectra, and mitigates variations from unknown changes in plasma temperature. © OSA 2013. ... Full text Cite

Multiple instance hidden markov models for GPR-based landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2013 Ground Penetrating Radar (GPR) is a widely used technology for the detection of subsurface buried threats. Although GPR data contains a representation of 3D space, during training, target and false alarm locations are usually only provided in 2D space alon ... Full text Cite

Application of image categorization methods for buried threat detection in GPR data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2013 Utilizing methods from the image processing and computer vision fields has led to advances in high resolution Ground Penetrating Radar (GPR) based threat detection. By analyzing 2-D slices of GPR data and applying various image processing algorithms, it is ... Full text Cite

Sparse model inversion and processing of spatial frequency-domain electromagnetic induction sensor array data for improved landmine discrimination

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2013 Frequency-domain electromagnetic induction (EMI) sensors have been shown to provide target signatures which enable discrimination of landmines from harmless clutter. In particular, frequency-domain EMI sensors are well-suited for target characterization by ... Full text Cite

A novel framework for processing forward looking infrared imagery with application to buried threat detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2013 Forward Looking Infrared (FLIR) cameras have recently been studied as a sensing modality for use in buried threat detection systems. FLIR-based detection systems benefit from larger standoff distances and faster rates of advance than other sensing modaliti ... Full text Cite

Computer vision techniques for target detection in ground penetrating radar data

Conference Proceedings of the IASTED International Conference on Signal and Image Processing Sip 2012 · December 1, 2012 Advances in ground penetrating radar (GPR) design, fabrication, and related signal processing have led to GPR becoming a powerful technology for the detection and identification of subsurface explosive threats. GPR's sensitivity to non-metallic disturbance ... Full text Cite

Chemometrics and machine learning for spectral analysis

Conference Laser Applications to Chemical, Security and Environmental Analysis, LACSEA 2012 · January 1, 2012 In this talk, we will review the current state of the art chemometric data processing techniques for LIBS and will highlight techniques we believe hold promise for improving detection and identification using LIBS spectra. © 2012 OSA. ... Cite

Multiple Instance Learning for Landmine Detection using GPR

Conference DETECTION AND SENSING OF MINES, EXPLOSIVE OBJECTS, AND OBSCURED TARGETS XVII · 2012 Full text Link to item Cite

Chemometrics and machine learning for spectral analysis

Conference Laser Applications to Chemical Security and Environmental Analysis Lacsea 2012 · January 1, 2012 In this talk, we will review the current state of the art chemometric data processing techniques for LIBS and will highlight techniques we believe hold promise for improving detection and identification using LIBS spectra. © 2012 OSA. ... Full text Cite

Histogram of gradient features for buried threat detection in ground penetrating radar data

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2012 Detection of buried explosive threats is a challenging problem. GPR has recently become a powerful tool for achieving robust subsurface target detection, but novel target types, and large numbers of subsurface objects in rural environments significantly co ... Full text Cite

Investigation of the effects of operator technique on handheld sensor data for landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 Ground penetrating radar (GPR) is a commonly employed sensing modality for landmine detection. It has been successfully deployed in vehicular systems, and is also being integrated into handheld systems. Handheld mine detection systems are typically deploye ... Full text Cite

Integration of lidar with the NIITEK GPR for improved performance on rough terrain

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 Vehicle-mounted ground-penetrating radar (GPR) has proved to be a valuable technology for buried threat detection, especially in the area of military route clearance. However, detection performance may be degraded in very rough terrain or o-road conditions ... Full text Cite

Keypoint-based image processing for landmine detection in GPR data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 Image keypoints are widely used in computer vision for object matching and recognition, where they provide the best solution for matching and instance recognition of complex objects within cluttered images. Most matching algorithms operate by rst nding int ... Full text Cite

Processing forward-looking data for anomaly detection: Single-look, multi-look, and spatial classification

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 Many effective buried threat detection systems rely on close proximity and near vertical deployment over subsurface objects before reasonable performance can be obtained. A forward-looking sensor configuration, where an object can be detected from much gre ... Full text Cite

A Bayesian method for discriminative context-dependent fusion of GPR-based detection algorithms

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 Ground-penetrating radar (GPR) is a very useful technology for buried threat detection applications which is capable of identifying both metallic and non-metallic objects with moderate false alarm rates. Several pattern classication algorithms have been pr ... Full text Cite

Rapid position estimation and tracking for autonomous driving

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 A method is presented for determining the position and orientation of a vehicle from a single, color video taken from the hood of the vehicle, for the purpose of assisting its autonomous operation at very high speeds on rural roads. An implicit perspective ... Full text Cite

Feature extraction and processing of spatial frequency-domain electromagnetic induction sensor data for improved landmine discrimination

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 Frequency-domain electromagnetic induction (EMI) sensors have been shown to provide target signatures which enable discrimination of landmines from harmless clutter. In particular, frequency-domain EMI sensors are well-suited for target characterization by ... Full text Cite

Change-based threat detection in urban environments with a forward-looking camera

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2012 Roadside explosive threats continue to pose a significant risk to soldiers and civilians in conflict areas around the world. These objects are easy to manufacture and procure, but due to their ad hoc nature, they are difficult to reliably detect using stan ... Full text Cite

A comparison of principal components and endmember-based contextual learning for hyperspectral anomaly classification

Conference Workshop on Hyperspectral Image and Signal Processing Evolution in Remote Sensing · December 28, 2011 Context-dependent learning algorithms have shown improved performance for anomaly classification in hyperspectral imagery (HSI) collected over varying environmental conditions. Past techniques have relied on statistically-motivated decomposition, such as p ... Full text Cite

Signal processing for the detection of explosive residues on varying substrates using laser induced breakdown spectroscopy

Conference Proceedings of SPIE the International Society for Optical Engineering · July 21, 2011 Laser induced breakdown spectroscopy (LIBS) can provide rapid, minimally destructive, chemical analysis of substances with the benefit of little to no sample preparation. Therefore, LIBS is a viable technology for the detection of substances of interest in ... Full text Cite

Multiple instance learning framework for landmine detection using ground penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 Ground Penetrating Radar (GPR) data provides a powerful technique to identify subsurface buried threats. Although GPR data contains a three-dimensional representation of the subsurface, object truth (i.e. labels and positions of true threat objects in trai ... Full text Cite

Exploiting spectral content for image segmentation in GPR data

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 Ground-penetrating radar (GPR) sensors provide an effective means for detecting changes in the sub-surface electrical properties of soils, such as changes indicative of landmines or other buried threats. However, most GPR-based pre-screening algorithms onl ... Full text Cite

Physics-based features for identifying contextual factors affecting landmine detection with ground-penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 It has been established throughout the ground-penetrating radar (GPR) literature that environmental factors can severely impact the performance of GPR sensors in landmine detection applications. Over the years, electromagnetic inversion techniques have bee ... Full text Cite

Frequency-domain electromagnetic induction sensor data feature extraction and processing for improved landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 Frequency-domain electromagnetic induction (EMI) sensors have the ability to provide target signatures which enable discrimination of landmines from harmless clutter. In particular, frequency-domain EMI sensors are well-suited for target characterization b ... Full text Cite

Classification of acoustic gunshot signatures using a nonparametric Bayesian signal model

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 The classification of firearms from their acoustic signatures has many potential benefits for a variety of military and security operations. Most approaches to acoustic gunshot classification can be characterized as frame based feature classification appro ... Full text Cite

Contextual learning in ground-penetrating radar data using Dirichlet process priors

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 In landmine detection applications, fluctuation of environmental and operating conditions can limit the performance of sensors based on ground-penetrating radar (GPR) technology. As these conditions vary, the classification and fusion rules necessary for a ... Full text Cite

Change detection for detecting potential threats in forward-looking video and downward-looking ground-penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 Forward looking video can provide a large amount of tactically-relevant information to vehicle operators regarding roadside explosive threats. However it is difficult for vehicle operators to keep track of what roadside objects have changed since their las ... Full text Cite

The Viterbi algorithm as an approach for incorporating spatial information into air/ground interface inference in GPR data

Conference Proceedings of SPIE the International Society for Optical Engineering · July 13, 2011 Rough surfaces present an impediment to the detection of buried threats with ground penetrating radar (GPR). Besides introducing artifacts in the sub-surface due to rough scattering, very rough or uneven surfaces can make inference of the location of the g ... Full text Cite

A hidden Markov context model for GPR-based landmine detection incorporating stick-breaking priors

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2011 In recent years, context-dependent algorithm fusion has been proposed for improving landmine detection with ground-penetrating radar (GPR) across changing environmental and operating conditions. While context-dependent fusion techniques generally assume in ... Full text Cite

Estimation of soil permittivity through autoregressive modeling of time-domain ground-penetrating radar data

Conference 2010 IEEE International Conference on Wireless Information Technology and Systems Icwits 2010 · December 7, 2010 Recent advances in context-dependent processing for vehicle-based route clearance suggest that information regarding the environmental context associated with ground-penetrating radar (GPR) data can potentially be exploited to improve target detection perf ... Full text Cite

Sparse model representations of target signatures for improved landmine detection using frequency-domain electromagnetic induction sensors

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 2010 Frequency-domain electromagnetic induction (EMI) sensors have the ability to measure target signatures which enable discrimination of landmines from harmless clutter. In a model-based signal processing paradigm, the target signatures can be decomposed into ... Full text Cite

Fusion of ground-penetrating radar and electromagnetic induction sensors for landmine detection and discrimination

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 2010 Ground penetrating radar (GPR) and electromagnetic induction (EMI) sensors provide complementary capabilities in detecting buried targets such as landmines, suggesting that the fusion of GPR and EMI modalities may provide improved detection performance ove ... Full text Cite

Information-based sensor management for the intelligent tasking of ground penetrating radar and electromagnetic induction sensors in landmine detection pre-screening

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 2010 Previous work has introduced a framework for information-based sensor management that is capable of tasking multiple sensors searching for targets among a set of discrete objects or in a cell grid. However, in many real-world scenarios - such as detecting ... Full text Cite

Nonparametric Bayesian time-series modeling and clustering of time-domain ground penetrating radar landmine responses

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 2010 Time domain ground penetrating radar (GPR) has been shown to be a powerful sensing phenomenology for detecting buried objects such as landmines. Landmine detection with GPR data typically utilizes a feature-based pattern classification algorithm to discrim ... Full text Cite

Dirichlet process based context learning for mine detection in hyperspectral imagery

Conference 2nd Workshop on Hyperspectral Image and Signal Processing Evolution in Remote Sensing Whispers 2010 Workshop Program · November 29, 2010 Hyperspectral imagery (HSI) has been shown to be a powerful remote sensing phenomenology that is appropriate for a variety of classification and detection tasks. Standard detection and classification algorithms applied to hyperspectral data are hindered by ... Full text Cite

Phenomenolgical model inversion with fisher information metrics for unexploded ordnance detection

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2010 Many of the ongoing efforts to develop strategies for detecting and locating subsurface unexploded ordnance (UXO) use features based on phenomenological models to discriminate between UXO and harmless clutter. The process of generating features requires mo ... Full text Cite

Context-dependent landmine detection with ground-penetrating radar using a hidden Markov context model

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2010 Context-dependent approaches to landmine detection have been developed in recent years to exploit the sensitivity of ground-penetrating radar (GPR) to changes in environmental conditions. Previous approaches to context-dependent fusion have only considered ... Full text Cite

Spatial latency reduction in GPR processing using stochastic sampling

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2010 Ground penetrating radar (GPR) is a promising technique for buried threat detection which provides a complimentary phenomenology to electro-magnetic induction (EMI) based sensing. However, many successful GPR-based buried threat detection algorithms requir ... Full text Cite

Identifying channel-specific impairments in cochlear implant patients via partial least squares discriminant analysis of speech-token confusion matrices

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2010 It is not uncommon for cochlear implant patients to have individual electrodes that produce anomalous percepts that impair or prevent the effective transmission of auditory information. Exhaustive psychophysical testing to detect all such information chann ... Full text Cite

Multiple instance and context dependent learning in hyperspectral data

Conference Whispers 09 1st Workshop on Hyperspectral Image and Signal Processing Evolution in Remote Sensing · December 21, 2009 Hyperspectral imaging (HSI) is a powerful tool for various remote sensing tasks including agricultural modeling and land-mine/unexploded ordnance clearance. Although the application of standard supervised learning techniques to HSI data has previously been ... Full text Cite

Integrating sensing and information processing in an electrical and computer engineering undergraduate curriculum

Conference Proceedings Frontiers in Education Conference Fie · December 1, 2009 The Department of Electrical and Computer Engineering Duke University has completed a full-scale redesign of its undergraduate program based on the theme of Integrated Sensing and Information Processing. This theme provides a coherent, overarching framewor ... Full text Cite

A graphical user interface for real-time spectroscopy: Software architecture for data collection, feature extraction, model development, and real-time testing

Conference Proceedings of SPIE the International Society for Optical Engineering · September 8, 2009 Recent advances in Laser-Induced breakdown spectroscopy (LIBS), Raman spectroscopy, and other spectroscopic approaches have increased interest in the application of spectroscopy to detection of explosives along with other chemical-signature identification ... Full text Cite

Sensor management using a new framework for observation modeling

Conference Proceedings of SPIE the International Society for Optical Engineering · September 8, 2009 In previous work, a sensor management framework has been developed that manages a suite of sensors in a search for static targets within a grid of cells. This framework has been studied for binary, non-binary, and correlated sensor observations, and the se ... Full text Cite

Bayesian detection of acoustic muzzle blasts

Conference Proceedings of SPIE the International Society for Optical Engineering · September 8, 2009 Acoustic detection of gunshots has many security and military applications. Most gunfire produces both an acoustic muzzle-blast signal as well as a high-frequency shockwave. However some guns do not propel bullets with the speed required to cause shockwave ... Full text Cite

Realtime gaussian markov random field based ground tracking for ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · September 8, 2009 Current ground penetrating radar algorithms for landmine detection require accurate estimates of the location of the air/ground interface to maintain high levels of performance. However, the presence of surface clutter, natural soil roughness, and antenna ... Full text Cite

Context-dependent feature selection for landmine detection with ground-penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · September 8, 2009 We present a novel method for improving landmine detection with ground-penetrating radar (GPR) by utilizing a priori knowledge of environmental conditions to facilitate algorithm training. The goal of Context-Dependent Feature Selection (CDFS) is to mitiga ... Full text Cite

Comparison of a distance-based likelihood ratio test and k-nearest neighbor classification methods

Conference Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing Mlsp 2008 · December 1, 2008 Several studies of the k-nearest neighbor (KNN) classifier have proposed the use of non-uniform weighting on the k neighbors. It has been suggested that the distance to each neighbor can be used to calculate the individual weights in a weighted KNN approac ... Full text Cite

Investigating the influence of pulse rate and duration on pitch perception in cochlear implants

Conference Proceedings European Conference on Noise Control · December 1, 2008 Multi-rate sound processing strategies may potentially provide improved speech recognition and music perception in cochlear implants, although it may be necessary to tune these strategies using psychophysical data to provide maximum benefit to the user. To ... Cite

Information-based sensor management for landmine detection using electromagnetic induction, ground-penetrating radar, and seismic sensors

Conference Proceedings European Conference on Noise Control · December 1, 2008 An information-based sensor management framework is discussed that enables the automated tasking of a suite of sensors when detecting static targets. The sensor manager chooses the sensors to use and the grid-based locations to observe in order to maximize ... Cite

Online SNR detection for dynamic power management in wireless ad-hoc networks

Conference Prime 2008 Phd Research in Microelectronics and Electronics Proceedings · September 22, 2008 Power consumption is a critical factor that determines the lifetime of a wireless network node. Substantial portion of the power is consumed by the transceiver in the transmit phase. This paper presents a new SNR detection technique for dynamic power manag ... Full text Cite

Performance comparison of frequency domain quadrupole and dipole electromagnetic induction sensors in a landmine detection application

Conference Proceedings of SPIE the International Society for Optical Engineering · June 2, 2008 This work provides a performance comparison between two frequency-domain electromagnetic induction (EMI) sensors - one quadrupole and one dipole sensor for the detection of subsurface anti-personnel and anti-tank landmines. A summary of the physical differ ... Full text Cite

Application of Markov random fields to landmine discrimination in ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · June 2, 2008 Recent advances in ground penetrating radar (GPR) design and fabrication have resulted in improved fidelity responses from relatively small, shallow-buried objects like landmines and improvised explosive devices. As the responses measured with GPR improve, ... Full text Cite

Sensor management for landmine detection using correlated sensor observations

Conference Proceedings of SPIE the International Society for Optical Engineering · June 2, 2008 Previous research has developed an information-theoretic sensor management framework for improving static target detection performance. This framework has been successfully applied to a large dataset of real landmine data; performance using the sensor mana ... Full text Cite

Statistical models for landmine detection in ground penetrating radar: Applications to synthetic data generation and pre-screening

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2008 As ground penetrating radar phenomenology continues to improve, more advanced statistical signal processing approaches become applicable to subsurface inference in GPR data. Despite the wide body of literature exploring the applications of various approach ... Full text Cite

Analysis of an information-based sensor manager applicable to landmine detection

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2008 Previously, a framework for sensor management has been developed for the detection of static targets such as landmines. The sensor manager functions by tasking the available sensors to greedily maximize the expected information gain obtained with each new ... Full text Cite

Matching pursuits decomposition for discrimination of unexploded ordnance: Isolated and overlapping signatures

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2008 A method of generating features for classification of unexploded ordnance using matching pursuits decomposition is proposed as a possible alternative, or complement, to the use of a standard dipole model. The proposed matching pursuit decomposition with an ... Full text Cite

Sensor management for static target detection with non-binary sensor observations and observation uncertainty

Conference IEEE Workshop on Statistical Signal Processing Proceedings · December 1, 2007 Previously, a grid-based sensor management framework has been developed that is useful for directing the operation of a suite of sensors seeking to detect static targets. Earlier versions of the framework only allow the sensors to make binary observations ... Full text Cite

Managing landmine detection sensors: Results from application to AMDS data

Conference Proceedings of SPIE the International Society for Optical Engineering · November 15, 2007 Previous work by the authors using information-based sensor management for static target detection has utilized a probability of error performance metric that assumes knowledge of the number of targets present in a grid of cells. Using this probability of ... Full text Cite

Performance of a four parameter model for modeling landmine signatures in frequency domain wideband electromagnetic induction detection systems

Conference Proceedings of SPIE the International Society for Optical Engineering · November 15, 2007 This work explores possible performance enhancements for landmine detection algorithms using frequency domain wideband electromagnetic induction sensors. A pre-existing four parameter model for conducting objects based on empirically collected data for UXO ... Full text Cite

Image segmentation techniques for improved processing of landmine responses in ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · November 15, 2007 As ground penetrating radar sensor phenomenology improves, more advanced statistical processing approaches become applicable to the problem of landmine detection in GPR data. Most previous studies on landmine detection in GPR data have focused on the appli ... Full text Cite

Ground bounce tracking for landmine detection using a sequential Monte Carlo method

Conference Proceedings of SPIE the International Society for Optical Engineering · November 15, 2007 A Sequential Monte Carlo (SMC) method is proposed to locate the ground bounce (GB) positions in 3D data collected by ground penetrating radar (GPR) system. The algorithm is verified utilizing real data and improved landmine detection performance is achieve ... Full text Cite

Experiment, explore, design: A sensor-based introductory ECE laboratory

Conference ASEE Annual Conference and Exposition Conference Proceedings · January 1, 2007 A new introductory course, Fundamentals of Electrical and Computer Engineering (ECE), has been designed to provide a rigorous, integrated introduction to the ECE field. The course laboratory, described in this paper, both promotes concept integration and p ... Cite

Experiment, explore, design: A sensor-based introductory ECE laboratory

Conference ASEE Annual Conference and Exposition, Conference Proceedings · 2007 A new introductory course, Fundamentals of Electrical and Computer Engineering (ECE), has been designed to provide a rigorous, integrated introduction to the ECE field. The course laboratory, described in this paper, both promotes concept integration and p ... Cite

Identifying impaired cochlear implant channels via speech-token confusion matrix analysis

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2007 Cochlear implant patients exhibit a wide range of performance on speech recognition tasks. One potential explanation for such variability is the existence of psychophysically observed phenomena that might indicate the presence of anomalous percepts associa ... Full text Cite

Redesign of the core curriculum at Duke University

Conference ASEE Annual Conference and Exposition, Conference Proceedings · December 1, 2006 Cite

A novel introductory course for teaching the fundamentals of electrical and computer engineering

Conference ASEE Annual Conference and Exposition, Conference Proceedings · December 1, 2006 The Electrical and Computer Engineering (ECE) department at Duke University is undergoing extensive curriculum revisions incorporating both new content and organization and innovative teaching methods. The cornerstone of the new curriculum is a theme-based ... Cite

Sensor management with uncertain performance characteristics

Conference 2006 IEEE Sensor Array and Multichannel Signal Processing Workshop Proceedings SAM 2006 · December 1, 2006 Previous work has presented an information-theoretic sensor management framework for the detection of static targets. This framework is based on the expected discrimination gain maximization technique of Kastella. The sensor manager searches for N targets ... Cite

Constrained filter optimization for subsurface landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · August 23, 2006 Previous large-scale blind tests of anti-tank landmine detection utilizing the NIITEK ground penetrating radar indicated the potential for very high anti-tank landmine detection probabilities at very low false alarm rates for algorithms based on adaptive b ... Full text Cite

Comparison of pattern recognition approaches for multi-sensor detection and discrimination of anti-personnel and anti-tank landmines

Conference Proceedings of SPIE the International Society for Optical Engineering · August 23, 2006 In this work we explore and compare several statistical pattern recognition techniques for classification and identification of buried landmines using both electromagnetic induction and ground penetrating radar data. In particular we explore application of ... Full text Cite

The effects of uncertainty and uncertainty modeling on information-based sensor manager performance

Conference Proceedings of SPIE the International Society for Optical Engineering · August 23, 2006 A proliferation of the number and variety of sensors for the landmine detection problem has created the need for a sensor manager that is able to intelligently task and coordinate the operation of a suite of landmine sensors. Previous work has developed a ... Full text Cite

Redesign of the core curriculum at Duke University

Conference ASEE Annual Conference and Exposition Conference Proceedings · January 1, 2006 Cite

A novel introductory course for teaching the fundamentals of electrical and computer engineering

Conference ASEE Annual Conference and Exposition Conference Proceedings · January 1, 2006 The Electrical and Computer Engineering (ECE) department at Duke University is undergoing extensive curriculum revisions incorporating both new content and organization and innovative teaching methods. The cornerstone of the new curriculum is a theme-based ... Cite

Information-theoretic sensor management for multimodal sensing

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2006 In recent years, sensor management algorithms have been studied for the purpose of providing intelligent, automated control of complex fielded sensor suites in remote sensing applications. In this paper, a framework for sensor management is presented that ... Full text Cite

Ground response tracking for improved landmine detection in ground penetrating radar data

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2006 Recent advances in ground penetrating radar (GPR) fabrication and signal processing have made high fidelity detection of buried anti-tank landmines a practical possibility under field scenarios. However, detection of subsurface landmines at a low false ala ... Full text Cite

Statistical and adaptive signal processing for UXO discrimination for next-generation sensor data

Conference Piers 2006 Cambridge Progress in Electromagnetics Research Symposium Proceedings · January 1, 2006 Until recently, detection algorithms could not reliably distinguish between buried UXO and clutter, leading to many false alarms. Over the last several years modern geophysical techniques have been developed that merge more sophisticated sensors, underlyin ... Full text Cite

Expediting the identification of impaired cochlear implant acoustic model channels through confusion matrix analysis

Conference 2nd International IEEE EMBS Conference on Neural Engineering · December 1, 2005 Psychophysical studies with cochlear implant patients have demonstrated performance variability across the electrode array, in some cases with electrodes displaying quite anomalous behavior. Aberrant cochlear implant channels have been linked to reduced sp ... Full text Cite

Application of matched subspace detectors to target detection and identification in ground penetrating radar data

Conference Proceedings of SPIE the International Society for Optical Engineering · October 24, 2005 In this work we present an application of matched subspace detectors to the problem of target detection and identification using ground penetrating radar data. In particular we apply sets of matched subspace detector filter banks to data containing both an ... Full text Cite

Information-based sensor management for landmine detection using multimodal sensors

Conference Proceedings of SPIE the International Society for Optical Engineering · October 24, 2005 We consider an information-theoretic approach for sensor management that chooses sensors and sensor parameters in order to maximize the expected discrimination gain associated with each new sensor measurement. We analyze the problem of searching for N targ ... Full text Cite

Multi-modal Iterative Adaptive Processing (MIAP) performance in the discrimination mode for landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · October 24, 2005 Due to the nature of landmine detection, a high detection probability (P d) is required to avoid casualties and injuries. However, high P d is often obtained at the price of extremely high false alarm rates. It is widely accepted that ... Full text Cite

Force Protection Demining System (FPDS) detection subsystem

Conference Proceedings of SPIE the International Society for Optical Engineering · October 24, 2005 This study describes the U.S. Army Force Protection Demining System (FPDS); a remotely-operated, multisensor platform developed for reliable detection and neutralization of both anti-tank and anti-personnel landmines. The ongoing development of the prototy ... Full text Cite

Analysis of wideband EMI field data

Conference Proceedings of SPIE the International Society for Optical Engineering · October 24, 2005 Last year, we reported on a preliminary evaluation of GE's frequency-domain EMI prototype sensor capable of measuring the wideband response of simulant and inert low metal mines at shallow depths over a frequency range from 100 Hz to 150 kHz. Since then, t ... Full text Cite

Feature selection for physics model based object discrimination

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2005 We investigated the application of two state-of-the-art feature selection algorithms for subsurface target discrimination. One is called joint classification and feature optimization (JCFO), which imposes a sparse prior on the features, and optimizes the c ... Full text Link to item Cite

Theme-based redesign of the duke university ECE curriculum: The first steps

Conference ASEE Annual Conference and Exposition, Conference Proceedings · 2005 Undergraduates in Electrical and Computer Engineering (ECE) at Duke University have benefited from the combination of curricular flexibility and rigorous coursework. The current curriculum is further limited in that the core courses do not offer a vertical ... Cite

Application and extension of texture feature coding methods to anti-tank landmine detection

Conference Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems Sageep · January 1, 2005 Recent advances in ground penetrating radar (GPR) fabrication and related signal processing have yielded robust performance on government sponsored blind tests of anti-tank landmine detection capabilities on test lanes. Recent data collections with the NII ... Full text Cite

Multisensor, remotely-operated force protection mine detection

Conference Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems Sageep · January 1, 2005 Despite improvements in both military and civilian mine detection equipment, humanitarian demining remains a slow, hazardous, and labor-intensive task. The Force Protection Demining System (FPDS) seeks to provide an efficient and reliable, teleoperated, mi ... Full text Cite

Uxo discrimination using blind source separation

Conference Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems Sageep · January 1, 2005 Statistical signal processing techniques have shown progress in discriminating UXO from clutter when the objects occur in isolation. Under this condition, only a single object contributes to the sensor measurement. For multiple closely-spaced subsurface ob ... Full text Cite

A vertically-integrated application-driven signal processing laboratory

Conference ASEE Annual Conference and Exposition Conference Proceedings · January 1, 2005 Hardware-based laboratories have been successfully integrated into individual Digital Signal Processing (DSP) courses at many universities. Typically, most hardware-based DSP laboratory experiences are offered to upper-level students and focus on programmi ... Cite

The efficacy of human observation for discrimination and feature identification of targets measured by the NIITEK ground penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 Recently, blind tests of several automated detection algorithms operating on the NIITEK ground penetrating radar data (GPR) have resulted in quite promising performance results. Anecdotally, human observers have also shown notable skill in detecting landmi ... Full text Cite

Feature-based processing of pre-screener generated alarms for performance improvements in target identification using the niitek ground-penetrating radar system

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 In this paper we present a multi-stage algorithm for target/clutter discrimination and target identification using the Niitek/Wichmann ground penetrating radar (GPR). To identify small subsets of GPR data for feature-processing, a pre-screening algorithm b ... Full text Cite

Landmine discrimination via Bayesian adaptive multi-modal processing: Results for handheld and vehicular sensors

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 The recent development of high quality sensors paired with development of advanced statistical signal processing algorithms has shown that there are sensors that can not only discriminate targets from clutter, but can also identify subsurface or obscured t ... Full text Cite

Three dimensional features to improve detection using ground penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 Two new features are presented to improve the detection of Anti-Tank (AT) landmines using Ground Penetrating Radar (GPR). A simplified three dimensial physics based model is used as the basis for the features. We combine these features with the results of ... Full text Cite

Parameterized likelihood ratio method for EMI unexploded ordnance detection

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 With current signal processing techniques, successful discrimination between UXO (Unexploded Ordnance) and clutter depends on characteristics that are consistent across all examples of an ordnance type. Real UXO, however, exhibit many differences from inst ... Full text Cite

Man versus machine: Robust regional processing of EMI data

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 The handheld F3 metal detector, developed by the MineLab Corporation, measures the responses of buried objects to electromagnetic pulses. These responses can be processed to determine whether a landmine is present. The simplest processor calculates the tot ... Full text Cite

Signal processing for improved explosives detection using quadrupole resonance

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 Quadrupole resonance (QR) technology for explosives detection is of crucial importance in an increasing number of applications. For landmine detection, where the detection system cannot be adequately shielded, QR has proven to be highly effective if the QR ... Full text Cite

Data analysis for classification of UXO filler using pulsed neutron techniques

Conference Proceedings of SPIE the International Society for Optical Engineering · December 20, 2004 Irradiating substances with pulsed neutrons results in several types of interactions which cause the emission of gamma rays. The energy of these gamma rays is characteristic of the nuclei with which the reaction occurred, and can therefore be used as an in ... Full text Cite

Work in progress: Theme-based redesign of an electrical and computer engineering curriculum

Conference Proceedings Frontiers in Education Conference Fie · December 1, 2004 The goal of this work-in-progress is to develop an innovative ECE curriculum that focuses on ECE fundamentals within the construct of real-world integrated system design, analysis, and problem solving. The curriculum will be formulated around the theme of ... Cite

Predicting vowel and consonant confusions using signal processing techniques

Conference International Congress Series · November 2004 Full text Cite

Dynamic range and intensity discrimination with high-rate pulse-train carriers: Predictions from a stochastic model and comparison with performance for noise-modulated pulse-train stimuli

Conference International Congress Series · November 1, 2004 This work investigates the properties of the neural response to a low frequency sinusoidal signal with a high-rate pulse-train carrier using a stochastic auditory nerve model. The agreement between the theoretical predictions, model simulations, and psycho ... Full text Cite

Vowel and consonant confusion in noise by cochlear implant subjects: Predicting performance using signal processing techniques

Conference ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · September 27, 2004 Cochlear implants are able to restore some degree of hearing to deafened individuals; however implant users are particularly susceptible to background noise. The effect of noise can be assessed using vowel and consonant confusions measured in listening exp ... Cite

Theoretical prediction of dynamic range and intensity discrimination for electrical noise-modulated pulse-train stimuli

Conference ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · September 27, 2004 This work investigates dynamic range and intensity discrimination for electrical noise-modulated pulse-train stimuli using a stochastic auditory nerve model, Based on a hypothesized monotonic relationship between loudness and the number of spikes, theoreti ... Cite

Vowel and consonant confusion in noise by cochlear implant subjects: Predicting performance using signal processing techniques

Conference ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · 2004 Cochlear implants are able to restore some degree of hearing to deafened individuals; however implant users are particularly susceptible to background noise. The effect of noise can be assessed using vowel and consonant confusions measured in listening exp ... Cite

Theoretical prediction of dynamic range and intensity discrimination for electrical noise-modulated pulse-train stimuli

Conference ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings · 2004 This work investigates dynamic range and intensity discrimination for electrical noise-modulated pulse-train stimuli using a stochastic auditory nerve model, Based on a hypothesized monotonic relationship between loudness and the number of spikes, theoreti ... Cite

Application of texture feature classification methods to landmine / clutter discrimination in off-lane GPR data

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2004 Recent advances in ground penetrating radar (GPR) fabrication and algorithm development have yielded significant performance improvements for anti-tank landmine detection in government sponsored blind tests. However these blind tests are typically conducte ... Full text Cite

Application of the LMS Algorithm to Anomaly Detection Using the Wichmann/Niitek Ground Penetrating Radar

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 This paper describes the application of a 2-dimensional (2-D) lattice LMS algorithm for anomaly detection using the Wichmann/Niitek ground penetrating radar (GPR) system. Sets of 3-dimensional (3-D) data are collected from the GPR system and these are proc ... Full text Cite

A comparison of neural networks and sub-space detectors for the discrimination of low-metal content landmines

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 Low-metal content landmines can be particularly difficult to detect and classify with electromagnetic induction (EMI) systems. Their responses are often less than that of indigenous clutter and the small amounts of asymmetrically distributed metal results ... Full text Cite

Separation of overlapping signatures in EMI data

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 Due to an object's unique combination of several physical characteristics, including conductivity and permeability, detection systems using the principles of electromagnetic induction (EMI) can be used to detect and classify a characteristic shape or signa ... Full text Cite

Adaptive Multi-Modality Processing for the Discrimination of Landmines

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 As in many application areas, performance of landmine detection algorithms is judged in terms of detection and false alarm rates. It is widely accepted that single sensors cannot simultaneously achieve both high detection rates and low false alarm rates, s ... Full text Cite

Physics model based unexploded ordnance discrimination using wideband EMI data

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 Unexploded ordnance (UXO) discrimination is investigated using the wide band electromagnetic induction (EMI) data. The main focus of this paper is on the practical phenomenological modeling for the induced wideband EMI sensor response from different target ... Full text Cite

Model-Based Statistical Signal Processing for UXO Discrimination: Performance Results from the JPG-V Demonstration

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 Detection and remediation of unexploded ordnance (UXO) represents a major challenge. The detection problem is exacerbated by the fact that on sites contaminated with UXO, extensive surface and sub-surface clutter and shrapnel is also present. Traditional m ... Full text Cite

Optimal Multisensor Decision Fusion of Mine Detection Algorithms

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 Numerous detection algorithms, using various sensor modalities, have been developed for the detection of mines in cluttered and noisy backgrounds. The performance for each detection algorithm is typically reported in terms of the Receiver Operating Charact ... Full text Cite

Region processing of EMI data for landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 A hand-held mine detector has two modes of operation: search and localization. In search mode, the goal is to identify areas where a buried mine might be located. Since minimizing the number of misses is a top priority, many regions identified in this mode ... Full text Cite

Correcting GPS Measurement Errors Induced by System Motion over Uneven Terrain

Conference Proceedings of SPIE the International Society for Optical Engineering · November 26, 2003 Many cart- and vehicular-based UXO detection systems employ GPS receivers to accurately determine the system's position. However, the unevenness of the terrain often causes the system to tilt during the data collection, introducing errors in the GPS measur ... Full text Cite

Stochastic resonance in the electrically stimulated auditory nerve: Predictions using a stochastic model of neural responsiveness

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2003 The incorporation of low levels of noise into an electrical stimulus has been shown to improve auditory thresholds in human subjects. In this paper, thresholds for noise-modulated pulse-train stimuli are predicted by utilizing a stochastic neural-behaviora ... Full text Link to item Cite

Algorithms for landmine detection using the NIITEK ground penetrating radar

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2002 Ground penetrating radar has been proposed as an alternative sensor to classical electromagnetic induction techniques for the landmine detection problem. The NIITEK-Wichmann antenna provides a high frequency radar signal with very low noise levels followin ... Full text Cite

The performance of matched subspace detectors and support vector machines for induction-based landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2002 Wideband electromagnetic induction (EMI) data provides an opportunity to apply statistical signal processing techniques to potentially mitigate false alarm rates in landmine detection. This paper explores the applications of matched subspace detectors and ... Full text Cite

A comparison of algorithms for landmine detection and discrimination using ground penetrating radar

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2002 Ground penetrating radar (GPR) has been proposed as an effective sensing modality for reducing the excessively high false alarm rates often encountered in landmine detection applications. Ground penetrating radar is sensitive to discontinuities in the inte ... Full text Link to item Cite

Sensor fusion of EMI and GPR data for improved landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2002 It is widely accepted that single sensors cannot simultaneously achieve both high detection rates and low false alarm rates for the landmine detection problem. Thus, in this paper we consider the fusion of two types of sensors, electromagnetic induction (E ... Full text Cite

A parameter transformation for improved decay rate estimation

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2002 Decay rate estimation has been proposed as an effective method for landmine and unexploded ordnance (UXO) detection and discrimination when electromagnetic induction (EMI) sensors are employed. The phenomenological basis for this strategy is that every obj ... Full text Cite

Model-based statistical sensor fusion for unexploded ordnance detection

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2002 Detection and remediation of unexploded ordnance (UXO) represents a major challenge on closed, closing, and transferred military ranges as well as on active installations. The detection problem is exacerbated by the fact that on sites contaminated with UXO ... Cite

A theoretical analysis of the effects of auditory impairment on intensity discrimination

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2002 The effect of cochlear hearing loss on intensity discrimination has been experimentally investigated and reported in the literature. It has been observed that the impairment configuration has a significant effect on a subject's discrimination abilities. In ... Full text Cite

A parameter transformation and cramér-rao bounds for estimating decay rates from exponential signals

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2002 Weighted sums of decaying exponentials characterize the response of many physical systems. Therefore, accurate decay rate estimation is a goal in many diverse disciplines. In this paper, a parameter transformation which improves decay rate estimation is pr ... Cite

Landmine detection with nuclear quadrupole resonance

Conference International Geoscience and Remote Sensing Symposium IGARSS · January 1, 2002 Nuclear Quadrupole Resonance (NQR) technology for the detection of explosives is of crucial importance in an increasing number of applications. For landmine detection, NQR has proven to be highly effective if the NQR sensor is not exposed to radio frequenc ... Cite

Threshold prediction for noise-modulated electrical stimuli using a stochastic auditory nerve model: Implications for cochlear implants

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2002 The effect of a low level additive noise process on the input and output characteristics and threshold behavior of auditory nerves (ANs) is studied by means of a stochastic computational model. This paper derives the stochastic properties of the model inpu ... Full text Cite

Adaptive time delay estimation method with signal selectivity

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2002 A new adaptive time delay estimation method is proposed for highly curruptive environments based on the cyclostationary property of the source signal. The time delay operator is modeled as a finite impulse response filter. The new adaptive scheme is based ... Full text Cite

Model-based predictions of intensity discrimination for normal- and impaired-hearing listeners

Conference 7th International Conference on Spoken Language Processing ICSLP 2002 · January 1, 2002 Interpretation of psychophysical data from impaired-hearing individuals on intensity discrimination tasks has been confounded by the fact that some impaired individuals' performance is nearnormal in quiet, whereas for others, the difference limen is elevat ... Cite

Single sensor processing and sensor fusion for GPR and EMI data

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 2001 As in many areas, performance of landmine detection algorithms is judged in terms of detection and false alarm rates. For the landmine detection problem, it is often the case that detectors satisfy one requirement at the cost of poor performance with regar ... Full text Cite

Enhanced signal and auditory processing for landmine detection using EMI sensors

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 2001 Although the ability of EMI sensors to detect landmines has improved significantly, false alarm rate reduction remains a challenging problem. However, experienced operators can often discriminate mines from metallic clutter with the aid of an audio transdu ... Full text Cite

Model-based statistical signal processing using electromagnetic induction data for landmine detection and classification

Conference IEEE Workshop on Statistical Signal Processing Proceedings · December 1, 2001 Traditionally, electromagnetic induction (EMI) sensors are operated in the time-domain and the response strength is related to the amount of metal present in the object. These sensors have been used almost exclusively for landmine detection. Unfortunately, ... Cite

Signal processing of ground penetrating radar data for subsurface object detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2001 Ground penetrating radar (GPR) generates a cross-sectional profile of the soil by transmitting electromagnetic waves that reflect back in a manner associated with the electrical properties and geometry of the objects buried underground. The responses of th ... Full text Cite

A theoretical study of information transmission in the auditory system using signal detection theory: Frequency discrimination by normal and impaired systems

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 2001 In this paper, we have investigated the differences between normal and impaired auditory processing for a frequency discrimination task by analyzing the responses of a computational auditory model using signal detection theory. Two detectors, one using all ... Cite

Performance bounds for target identification using decay rates estimates from EMI measurements

Conference International Geoscience and Remote Sensing Symposium IGARSS · December 1, 2000 Decay rate estimation has been proposed as an effective method for landmine and unexploded ordnance (UXO) detection. The physical basis for this strategy is that every object in the target library possesses a unique set of decay rates. In theory, the chara ... Cite

Improving detection of low-metallic content landmines using EMI data

Conference International Geoscience and Remote Sensing Symposium IGARSS · December 1, 2000 EMI, or metal detector, sensors are used extensively to detect landmines. There is often a significant amount of metallic clutter present in the environment, thus EMI sensors that utilize traditional detection algorithms based solely on metal content suffe ... Cite

Time-domain metal detector and GPR data processing and fusion for landmine detection

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2000 Data taken by the Coleman Research Corporation (CRC) Handheld Standoff Mine Detection System (HSTAMIDS) at Fort A. P. Hill, VA. and Yuma, AZ, it is demonstrated that statistical signal processing techniques show improved performance over the conventional d ... Full text Link to item Cite

Predicting improved human auditory discrimination for landmine detection using EMI sensors

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2000 In this study, an attempt is made to optimize the presentation of information to the operator and to predict improved performance prior to extensive experimental testing. It is shown that by supplying the sensor response more appropriately to the listener, ... Full text Link to item Cite

Improved detection of low-metallic content landmines using EMI data

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2000 EMI sensors are used extensively to detect landmines, and operate by detecting the metal that is present in mines. However, mines vary in their construction from metal-cased varieties with a large mass of metal to plastic-cased varieties with minute amount ... Full text Link to item Cite

Detection and classification of landmine-like targets in a non-Gaussian noise environment

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2000 Many statistical signal processing approaches to target detection and classification assume the measurement is corrupted by independent, identically distributed (i.i.d.) white Gaussian noise. This common assumption often results in simpler, and less comput ... Full text Link to item Cite

Physics-based statistical signal processing for improved landmine detection and classification via decay rate estimation

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2000 Target discrimination via decay rate (pole) estimation has been proposed as an effective method for landmine and UXO detection. The physical basis for this strategy is that every object in the target library (i.e., landmine and/or UXO target) possesses a u ... Full text Link to item Cite

Improved detection of low-metallic content landmines using EMI data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2000 EMI sensors are used extensively to detect landmines, and operate by detecting the metal that is present in mines. However, mines vary in their construction from metal-cased varieties with a large mass of metal to plastic-cased varieties with minute amount ... Cite

Physics-based statistical signal processing for improved landmine detection and classification via decay rate estimation

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2000 Target discrimination via decay rate (pole) estimation has been proposed as an effective method for landmine and UXO detection. The physical basis for this strategy is that every object in the target library (i.e., landmine and/or UXO target) possesses a u ... Cite

Improved UXO detection via sensor fusion

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2000 Traditional algorithms for UXO remediation experience severe difficulties distinguishing buried targets from anthropic clutter, and in most cases UXO items are found amongst extensive surface clutter and shrapnel from ordnance operations. These problems re ... Full text Cite

Bayesian optimal classification of metallic objects: a comparison of time-domain and frequency-domain EMI performance

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2000 Traditionally, field EMI sensors are operated in the time-domain. The time-domain (TD) EMI sensor usually is a pulsed system. It contains both a transmitting coil and a receiving coil. After transmitting an excitation pulse, which generates the primary fie ... Cite

Statistical signal processing for detection of buried landmines using quadrupole resonance

Conference DETECTION AND REMEDIATION TECHNOLOGIES FOR MINES AND MINELIKE TARGETS V, PTS 1 AND 2 · 2000 Full text Link to item Cite

Detection and classification of landmine-like targets in a non-Gaussian noise environment

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 2000 Many statistical signal processing approaches to target detection and classification assume the measurement is corrupted by independent, identically distributed (i.i.d.) white Gaussian noise. This common assumption often results in simpler, and less comput ... Cite

Time-domain metal detector and GPR data processing and fusion for landmine detection

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2000 Data taken by the Coleman Research Corporation (CRC) Handheld Standoff Mine Detection System (HSTAMIDS) at Fort A. P. Hill, VA. and Yuma, AZ, it is demonstrated that statistical signal processing techniques show improved performance over the conventional d ... Cite

Predicting improved human auditory discrimination for landmine detection using EMI sensors

Conference Proceedings of SPIE - The International Society for Optical Engineering · 2000 In this study, an attempt is made to optimize the presentation of information to the operator and to predict improved performance prior to extensive experimental testing. It is shown that by supplying the sensor response more appropriately to the listener, ... Cite

Classification of buried metal objects using wideband frequency-domain electromagnetic induction responses: a comparison of optimal and sub-optimal processors

Conference International Geoscience and Remote Sensing Symposium IGARSS · December 1, 1999 A study is carried out to investigate sub-optimal detectors that continue to incorporate the physical nature of the wideband frequency-domain electromagnetic induction (EMI) signal, but are less computationally burdensome. In addition, a comparison is made ... Cite

Statistical signal processing techniques for the detection of low-metal landmines using EMI and GPR sensors (topic area: E.1)

Conference International Geoscience and Remote Sensing Symposium IGARSS · December 1, 1999 The Joint UXO Coordination Office (JUXOCO) at Ft. Belvoir, VA is sponsoring a series of experiments designed to establish a performance baseline for a variety of sensors. The purpose of these experiments is to determine if advanced algorithms are useful fo ... Cite

Effect of a Poisson 'internal noise' process on theoretical acoustic signal detectability

Conference IEEE ASSP Workshop on Applications of Signal Processing to Audio and Acoustics · December 1, 1999 Historically, theoretical predictions of human auditory perception have not agreed with experimental measurements. We have previously demonstrated that using signal detection theory to analyze the outputs of deterministic computational auditory models yiel ... Cite

Enhanced auditory processing for landmine detection using EMI sensors

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 1999 Although the ability of EMI sensors to detect landmines has improved significantly, false alarm rate reduction remains a challenging problem. Improvements have been achieved through development of optimal algorithms that exploit models of the underlying ph ... Cite

Signal processing for NQR discrimination of buried landmines

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 1999 Nuclear quadrupole resonance (NQR) is a technique that discriminates mines from clutter by exploiting unique properties of explosives, rather than the attributes of the mine that exist in many forms of anthropic clutter (e.g., metal content). After excitin ... Full text Cite

Single sensor processing and sensor fusion of GPR and EMI data for landmine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 1999 In our previous work, we have shown theoretically that a model-based Bayesian approach to the detection of landmines affords significant performance gains over standard thresholding techniques. These performance gains hold for both time- and frequency-doma ... Cite

Comparison using signal detection theory of the ability of two computational auditory models to predict experimental data

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 1999 In order to develop improved remediation techniques for hearing impairment, auditory researchers must gain a greater understanding of the relation between the psychophysics of hearing and the underlying physiology. One approach to studying the auditory sys ... Cite

Enhanced detection of landmines using broadband EMI data

Conference Proceedings of SPIE the International Society for Optical Engineering · January 1, 1999 EMI sensors are used extensively to detect landmines. These sensors operate by detecting the metal that is present in mines. However, mines vary in their construction from metal-cased varieties with a large mass of metal to plastic-cased varieties with min ... Cite

Wideband electromagnetic induction for metal-target identification: Theory, measurement, and signal processing

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 1998 A principal problem with traditional, narrowband EMI sensors involves target identification. As a consequence, in minefield or unexploded ordinance (UXO) detection, for example, each piece of buried metal must be excavated, causing significant false alarms ... Full text Cite

Time-domain sensing of targets buried under a rough air-ground interface

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 1998 In this paper we model time-domain plane-wave scattering from targets buried under a rough (random) air-ground interface. The properties of the interface are parametrized as a random process with known statistics. Since the fields incident upon a buried ta ... Full text Cite

Improved signal processing approaches for land mine detection

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 1998 In our previous work, we have shown that a model-based Bayesian approach to the detection of mines affords significant performance gains for both time-domain and frequency-domain electromagnetic induction (EMI) sensor over standard thresholding techniques. ... Full text Cite

Hypothesis testing for landmine detection with EMI images

Conference 1998 IEEE International Conference on Fuzzy Systems Proceedings IEEE World Congress on Computational Intelligence · January 1, 1998 The goal of any landmine detection system is to achieve a high probability of detection while at the same time maintaining low probability of false alarm. For detection of landmines with electromagnetic induction (EMI) sensors, the performance tends to be ... Full text Cite

Improved decision-theoretic approach to the optimum detection of mines

Conference Proceedings of SPIE the International Society for Optical Engineering · December 1, 1997 The fundamental goal of mine detection is to achieve a high detection rate along with a low false alarm rate. While many mine detectors achieve the first of these goals, it is often at the cost of a prohibitively large false alarm rate. In this paper, a Ba ... Cite

Sensor fusion for mine detection with the RNN

Conference Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics · January 1, 1997 In this paper we propose a neural network based approach to sensor fusion, to detect mine locations from electromagnetic induction (EMI) data. Our results use the Random Neural Network (RNN) model [2, 4, 5] which is closer to biophysical reality and mathem ... Full text Cite

A multiresolution generalized likelihood ratio detection approach to target screening in synthetic aperture radar data

Conference Proc. SPIE - Int. Soc. Opt. Eng. (USA) · 1995 We present a detection concept for initial target screening based on features that are derived from a multiresolution decomposition of synthetic aperture radar (SAR) data. The physical motivation of the multiresolution feature based approach is the exploit ... Cite

Multiresolution target detection in SAR imagery

Conference ICASSP IEEE International Conference on Acoustics Speech and Signal Processing Proceedings · January 1, 1995 We demonstrate the utility of a multiresolution approach for target detection in SAR imagery. Man-made objects exhibit characteristic phase and amplitude fluctuations as the image resolution is varied, while natural terrain has a random signature. We const ... Cite

Multiresolution detection of coherent radar targets

Conference Proceedings International Conference on Image Processing Icip · January 1, 1994 Examines the problem of detecting a known target in clutter and shows that a multiresolution-based detector significantly outperforms a more conventional single-resolution detector. The authors then apply a sampling strategy that allows one to choose, for ... Full text Cite

A multiresolution approach to target detection in synthetic aperture radar data

Conference Conference Record Asilomar Conference on Signals Systems and Computers · January 1, 1994 We demonstrate the utility of a multiresolution approach for target detection in SAR imagery. In particular, man-made objects exhibit characteristic phase and amplitude fluctuations as the image resolution is varied, while natural terrain (i.e., clutter) h ... Full text Cite