Rabih Younes

Conference Proceedings Frontiers in Education Conference Fie · January 1, 2025 This work-in-progress research-to-practice paper presents an early-stage study aimed at advancing meaningful industry engagement in undergraduate engineering education. While such collaborations offer clear benefits for student motivation, skill developmen ... Full text Cite

Predicting Student Performance Using Discussion Forums' Participation Data

Conference ASEE Annual Conference and Exposition Conference Proceedings · June 23, 2024 A significant gap in education lies in the need for mechanisms that enable early detection of potentially at-risk students. Through access to an earlier prediction of student performance, instructors are given ample time to meet with and assist under-achie ... Cite

Self-supervised Multi-Modal Video Forgery Attack Detection

Conference IEEE Wireless Communications and Networking Conference Wcnc · January 1, 2023 Video forgery attacks threaten surveillance systems by replacing the video captures with unrealistic synthesis, which can be powered by the latest augmented reality and virtual reality technologies. From the machine perception aspect, visual objects often ... Full text Cite

Real-time Blind Deblurring Based on Lightweight Deep-Wiener-Network

Conference Proceedings of the International Joint Conference on Neural Networks · January 1, 2023 In this paper, we address the problem of blind image deblurring with high efficiency. We propose a set of lightweight deep-Wiener-networks to achieve the task with real-time speed. The network contains a deep neural network for estimating the parameters of ... Full text Cite

ResNet-Like CNN Architecture and Saliency Map for Human Activity Recognition

Conference Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst · January 1, 2022 Human activity recognition (HAR) has been adopting deep learning to substitute well-established analysis techniques that rely on hand-crafted feature extraction and classication techniques. However, the architecture of convolutional neural network (CNN) mo ... Full text Cite

Toward Data Augmentation and Interpretation in Sensor-Based Fine-Grained Hand Activity Recognition

Conference Communications in Computer and Information Science · January 1, 2021 Recognizing fine-grained hand activities has widely attracted the research community’s attention in recent years. However, rather than enriched sen-sor-based datasets of whole-body activities, there are limited data available for acceler-ator-based fine-gr ... Full text Cite

ActivityGAN: Generative adversarial networks for data augmentation in sensor-based human activity recognition

Conference Ubicomp Iswc 2020 Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers · September 10, 2020 Label Scarcity and Data Augmentation have long been challenging problems in the research of Human-oriented Artificial Intelligence. Following the trends of Deep Learning, Human Activity Recognition (HAR) tasks have been significantly optimized in the recen ... Full text Cite

Simple steps to lower student stress in a digital systems course while maintaining high standards and expectations

Conference ASEE Annual Conference and Exposition Conference Proceedings · June 22, 2020 Student stress is an important issue that is gaining more attention with time in our universities because of the increase in competition in every aspect of the educational process, from college admission to finding a good job that satisfies students' expec ... Cite

Toward practical activity recognition: Recognizing complex activities with wide variations

Conference Proceedings of the 2018 IEEE International Conference on Pervasive Computing and Communications · 2018 Most activity classifiers focus on recognizing application-specific activities that are mostly performed in a scripted manner, where there is very little room for variation within the activity. These classifiers are mainly good at recognizing short scripte ... Full text Link to item Cite

Activity classification at a higher level: what to do after the classifier does its best?

Conference Proceedings of the 2015 ACM International Symposium on Wearable Computers · 2015 Research in activity classification has focused on the sensors, the classification techniques and the machine learning algorithms used in the classifier. In this work, we study a higher level of activity classification. We present two methods that can take ... Full text Link to item Cite