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2005 IEEE International Conference on Multimedia and Expo
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
Amsterdam, Netherlands
July 06-July 06
ISBN: 0-7803-9331-7
null Chengcui Zhang, Department of Computer and Information Sciences, University of Alabama at Birmingham
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on One-Class Support Vector Machine (SVM) to solve MIL problem in the region-based Content Based Image Retrieval (CBIR). Relevance Feedback technique is incorporated to provide progressive guidance to the learning process. Performance is evaluated and the effectiveness of our retrieval algorithm has been shown through comparative studies.
Citation:
null Chengcui Zhang, null Xin Chen, null Min Chen, null Shu-Ching Chen, null Mei-Ling Shyu, "A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine," icme, pp.1142-1145, 2005 IEEE International Conference on Multimedia and Expo, 2005
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