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Proceedings Paper

Probabilistic SVM for open set automatic target recognition on high range resolution radar data
Author(s): Jason D. Roos; Arnab K. Shaw
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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
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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