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A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine

8 years 10 months ago
A Multiple Instance Learning Approach for Content Based Image Retrieval Using One-Class Support Vector Machine
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.
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICMCS
Authors Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen, Mei-Ling Shyu
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