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A bivariate gaussian model for unexploded ordnance classification with EMI data

Publication ,  Journal Article
Williams, D; Yu, Y; Kennedy, L; Zhu, X; Carin, L
Published in: IEEE Geoscience and Remote Sensing Letters
October 1, 2007

A bivariate Gaussian model is proposed for modeling spatially varying electromagnetic-induction (EMI) response of unexploded ordnance (UXO). This model is proposed for EMI sensors that do not exploit enough physics to warrant using the popular magnetic-dipole model currently commonly used. These two competing models are applied to measured EM61 sensor data at a real UXO site. UXO classification performance using the proposed bivariate Gaussian model is shown to be superior to an approach employing the magnetic-dipole model. Moreover, the bivariate Gaussian model requires no labeled training data, obviates classifier construction, and has fewer model parameters to learn. © 2007 IEEE.

Duke Scholars

Published In

IEEE Geoscience and Remote Sensing Letters

DOI

ISSN

1545-598X

Publication Date

October 1, 2007

Volume

4

Issue

4

Start / End Page

629 / 633

Related Subject Headings

  • Geological & Geomatics Engineering
  • 4013 Geomatic engineering
  • 3709 Physical geography and environmental geoscience
  • 3704 Geoinformatics
  • 0909 Geomatic Engineering
  • 0906 Electrical and Electronic Engineering
  • 0801 Artificial Intelligence and Image Processing
 

Citation

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Williams, D., Yu, Y., Kennedy, L., Zhu, X., & Carin, L. (2007). A bivariate gaussian model for unexploded ordnance classification with EMI data. IEEE Geoscience and Remote Sensing Letters, 4(4), 629–633. https://doi.org/10.1109/LGRS.2007.903972
Williams, D., Y. Yu, L. Kennedy, X. Zhu, and L. Carin. “A bivariate gaussian model for unexploded ordnance classification with EMI data.” IEEE Geoscience and Remote Sensing Letters 4, no. 4 (October 1, 2007): 629–33. https://doi.org/10.1109/LGRS.2007.903972.
Williams D, Yu Y, Kennedy L, Zhu X, Carin L. A bivariate gaussian model for unexploded ordnance classification with EMI data. IEEE Geoscience and Remote Sensing Letters. 2007 Oct 1;4(4):629–33.
Williams, D., et al. “A bivariate gaussian model for unexploded ordnance classification with EMI data.” IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 4, Oct. 2007, pp. 629–33. Scopus, doi:10.1109/LGRS.2007.903972.
Williams D, Yu Y, Kennedy L, Zhu X, Carin L. A bivariate gaussian model for unexploded ordnance classification with EMI data. IEEE Geoscience and Remote Sensing Letters. 2007 Oct 1;4(4):629–633.

Published In

IEEE Geoscience and Remote Sensing Letters

DOI

ISSN

1545-598X

Publication Date

October 1, 2007

Volume

4

Issue

4

Start / End Page

629 / 633

Related Subject Headings

  • Geological & Geomatics Engineering
  • 4013 Geomatic engineering
  • 3709 Physical geography and environmental geoscience
  • 3704 Geoinformatics
  • 0909 Geomatic Engineering
  • 0906 Electrical and Electronic Engineering
  • 0801 Artificial Intelligence and Image Processing