Relevance Feedback in Image Retrieval Based on RSVM

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 neednt use the results of retrieval to train SVM again as traditional method. Experimental results show that the model has good effectiveness.

关键词： support vector machines(SVM) incremental reduced support vector machines (IRSVM) image retrieval

作者: Ya-Li Qi

作者单位: Department of Computer Science Beijing Institute of Graphic Communication Beijing, China

会议类型: 国际会议

会议名称: 2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)

会议地点: 太原

会议语种:英文

页码: 228-231

在线出版日期: 2009-07-10（万方平台首次上网日期，不代表论文的发表时间）