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Proceedings Paper

Gaussian process classification using automatic relevance determination for SAR target recognition
Author(s): Xiangrong Zhang; Limin Gou; Biao Hou; Licheng Jiao
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Paper Abstract

In this paper, a Synthetic Aperture Radar Automatic Target Recognition approach based on Gaussian process (GP) classification is proposed. It adopts kernel principal component analysis to extract sample features and implements target recognition by using GP classification with automatic relevance determination (ARD) function. Compared with k-Nearest Neighbor, Naïve Bayes classifier and Support Vector Machine, GP with ARD has the advantage of automatic model selection and hyper-parameter optimization. The experiments on UCI datasets and MSTAR database show that our algorithm is self-tuning and has better recognition accuracy as well.

Paper Details

Date Published: 25 October 2010
PDF: 7 pages
Proc. SPIE 7830, Image and Signal Processing for Remote Sensing XVI, 78300R (25 October 2010); doi: 10.1117/12.864845
Show Author Affiliations
Xiangrong Zhang, Xidian Univ. (China)
Limin Gou, Xidian Univ. (China)
Biao Hou, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 7830:
Image and Signal Processing for Remote Sensing XVI
Lorenzo Bruzzone, Editor(s)

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