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Proceedings Paper

Ship target recognition using kernel Fisher discriminant
Author(s): Ying Li; Bendu Bai; Licheng Jiao
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Paper Abstract

The classification of ship targets using the kernel Fisher discriminant analysis is investigated in this paper. The main idea of this method is to find a nonlinear direction by first mapping the data nonlinearly into some feature space and compute Fisher's linear discriminant in input space. Based on the kernel Fisher discriminant, we recognize three types of ships. The satisfactory experimental results are obtained. In addition, we compare this method with other state of the art classification techniques. The experiments show that the kernel Fisher discriminant is superior to the other algorithms.

Paper Details

Date Published: 24 September 2001
PDF: 5 pages
Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); doi: 10.1117/12.441633
Show Author Affiliations
Ying Li, Xidian Univ. (China)
Bendu Bai, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 4554:
Object Detection, Classification, and Tracking Technologies
Jun Shen; Sharatchandra Pankanti; Runsheng Wang, Editor(s)

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