Papers Published

1. 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, vol. 4 no. 4 (October, 2007), pp. 629-633, Institute of Electrical and Electronics Engineers (IEEE) [doi] .
   (last updated on 2024/12/31)

   Abstract:
   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.