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Proceedings Paper

Transfer network learning based remote sensing target recognition
Author(s): Shuiping Gou; Yuqin Wang; Licheng Jiao
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Paper Abstract

The target recognition accuracy of remote sensing images is not satisfied. The labels of images acquisition and recollecting are difficult and expensive. In order to solve the problem, we introduce transfer learning into Network Boosting algorithm (NB) and propose Transfer Network Learning algorithm (TNL), in which other out-date data are reused to instruct the remote sensing target recognition. TNL is suitable to improve the performance of remote sensing target recognition, in which instances transfer learning is adopted for domain adaptation. The experimental results on the MSTAR SAR data set and remote sensing data set including two-class planes show that the proposed algorithm has better performance and achieves different domains learning.

Paper Details

Date Published: 30 October 2009
PDF: 8 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74950A (30 October 2009); doi: 10.1117/12.833583
Show Author Affiliations
Shuiping Gou, Xidian Univ. (China)
Yuqin Wang, Xidian Univ. (China)
Licheng Jiao, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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