Paper
25 October 2010 Gaussian process classification using automatic relevance determination for SAR target recognition
Xiangrong Zhang, Limin Gou, Biao Hou, Licheng Jiao
Author Affiliations +
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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiangrong Zhang, Limin Gou, Biao Hou, and Licheng Jiao "Gaussian process classification using automatic relevance determination for SAR target recognition", Proc. SPIE 7830, Image and Signal Processing for Remote Sensing XVI, 78300R (25 October 2010); https://doi.org/10.1117/12.864845
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Synthetic aperture radar

Target recognition

Databases

Automatic target recognition

Detection and tracking algorithms

Image classification

Image processing

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