TY - GEN
T1 - Active selection of labeled data for target detection
AU - Zhang, Yan
AU - Liao, Xuejun
AU - Dura, Esther
AU - Carin, Lawrence
N1 - Generated from Scopus record by KAUST IRTS on 2021-02-09
PY - 2004/9/27
Y1 - 2004/9/27
N2 - An information-theoretic approach is developed for target detection, with active selection of training set, directly from the site-specific measured data For the proposed kernel-based algorithm, a set of basis functions are defined first to characterize the signature distribution of the site, then we determine a parsimonious set of data, for which knowledge of the associated labels would be most informative to determine the weights for the basis functions. Both of them utilize the Fisher information criteria. The proposed framework is applied to subsurface target detection, with example results presented for an actual buried unexploded ordnance site.
AB - An information-theoretic approach is developed for target detection, with active selection of training set, directly from the site-specific measured data For the proposed kernel-based algorithm, a set of basis functions are defined first to characterize the signature distribution of the site, then we determine a parsimonious set of data, for which knowledge of the associated labels would be most informative to determine the weights for the basis functions. Both of them utilize the Fisher information criteria. The proposed framework is applied to subsurface target detection, with example results presented for an actual buried unexploded ordnance site.
UR - http://www.scopus.com/inward/record.url?scp=4544304352&partnerID=8YFLogxK
M3 - Conference contribution
BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ER -