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作者:

Zhou, Yihua (Zhou, Yihua.) | Shi, Weimin (Shi, Weimin.) | Duan, Lijuan (Duan, Lijuan.) (学者:段立娟) | Niu, Cuiying (Niu, Cuiying.)

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摘要:

A fixed SVM model setting is not suitable for the evolvement of the pattern of user's interest. In this paper a relevance feedback algorithm based on SVM model's dynamic adjusting for image retrieval is presented. In this algorithm, there is no need to fix the model's parameters beforehand, and the parameters of SVM model will be automatically adjusted corresponding to the changing of the training samples. Experimental results show the proposed algorithm outperformed other algorithms with fixed model's parameter. © 2007 IEEE.

关键词:

Intelligent computing Parameter estimation Image retrieval

作者机构:

  • [ 1 ] [Zhou, Yihua]College of Computer Sci. and Tech., Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Shi, Weimin]College of Computer Sci. and Tech., Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Duan, Lijuan]College of Computer Sci. and Tech., Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Niu, Cuiying]Beijing Longdachengxin Project Management Co.,Ltd., Beijing 100021, China

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来源 :

年份: 2007

页码: 287-290

语种: 英文

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SCOPUS被引频次: 5

ESI高被引论文在榜: 0 展开所有

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