Proceedings Paper
Probabilistic SVM for open set automatic target recognition on high range resolution radar data| Format | Member Price | Non-Member Price |
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Paper Abstract
The Eigen-Template (ET) based closed-set feature extraction approach is extended to an open-set HRR-ATR framework to develop an Open Set Probabilistic Support Vector Machine (OSP-SVM) classifier. The proposed ET-OSP-SVM is shown to perform open set ATR on HRR data with 80% PCC for a 4-class MSTAR dataset.
Paper Details
Date Published: 1 May 2017
PDF: 14 pages
Proc. SPIE 10202, Automatic Target Recognition XXVII, 102020B (1 May 2017); doi: 10.1117/12.2262840
Published in SPIE Proceedings Vol. 10202:
Automatic Target Recognition XXVII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)
PDF: 14 pages
Proc. SPIE 10202, Automatic Target Recognition XXVII, 102020B (1 May 2017); doi: 10.1117/12.2262840
Show Author Affiliations
Jason D. Roos, Wright State Univ. (United States)
Arnab K. Shaw, Wright State Univ. (United States)
Published in SPIE Proceedings Vol. 10202:
Automatic Target Recognition XXVII
Firooz A. Sadjadi; Abhijit Mahalanobis, Editor(s)
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