Relevance Feedback in Image Retrieval Based on RSVM

被引：0
|
作者：
Qi, Ya-Li [1 ]
机构：
[1] Beijing Inst Graph Commun, Dept Comp Sci, Beijing, Peoples R China
来源：
2009 WASE INTERNATIONAL CONFERENCE ON INFORMATION ENGINEERING, ICIE 2009, VOL I | 2009年
关键词：
support vector machines(SVM); incremental reduced support vector machines (IRSVM); image retrieval;
D O I：
10.1109/ICIE.2009.230
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Support vector machines (SVM) are favored for relevance feedback in content-based image retrieval by utilizing both positive and negative feedbacks. This paper uses Incremental Reduced Support Vector Machines to get the support vectors and the non-support vectors, then utilizes both positive and negative feedbacks for image retrieval based on SVM. It needn't use the results of retrieval to train SVM again as traditional method. Experimental results show that the model has good effectiveness
引用
收藏
页码：228 / 231
页数：4
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