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Proceedings Paper

A new artificial immune network classifier for SAR image
Author(s): Ruochen Liu; Manchun Niu
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Paper Abstract

Inspired by the idiotypic network theory, a new artificial immune network classifier for SAR image is proposed in this paper. In the proposed algorithm, only one B-cell instead of many B-cells is used to denote a class so as to reduce the scale of network as well as avoid the suppression operation between B-cells; moreover, a new affinity function based on the correct rate is proposed to realize antigen priority based the evaluation strategy. The proposed algorithm has been extensively compared with Fuzzy C-means (FCM), Multiple-Valued Immune Network algorithm (MVIN), and Clonal Selection Algorithm for classifier (CSA) over two SAR images. The result of experiment indicates the superiority of the algorithm over FCM, MVIN and CSA on classification accuracy and robustness.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74960W (30 October 2009); doi: 10.1117/12.832898
Show Author Affiliations
Ruochen Liu, Xidian Univ. (China)
Manchun Niu, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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