%0 Journal Article
%T Image retrieval using asymmetric bagging and FSVM<br>基于非对称打包和FSVM的图像检索
%A DENG Chang ge
%A ZHU Junzhu
%A YOU Qingcheng
%A GAO Ruru
%A <br>邓昌葛
%A 朱俊株
%A 尤庆成
%A 高如如
%J 中国图象图形学报
%D 2010
%I 
%X Recently, SVMs(support vector machines) have been widely used in image retrieval as a method to improve the retrieval performance. However, conventional SVMs encounter four problems: small size of positive samples, asymmetry problem of training samples, over-fitting and weakly real-time. To solve these problems, an asymmetric bagging based fuzzy support vector machine (AB-FSVM) is proposed. An asymmetric bagging is made to negative samples, and then based on fuzzy theory and SVM, the retrieval images are gotten. Experimental results based on a set of Corel images show that the proposed system performs much better than the previous methods, especially when the size of positive samples is small.
%K content-based image retrieval (CBIR)
%K asymmetric bagging (AB)
%K fuzzy support vector machine (FSVM)<br>基于内容的图像检索
%K 非对称打包
%K 模糊支持向量机
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=F7804A113AFA76C0E5C16E2D4C546098&yid=140ECF96957D60B2&vid=23CCDDCD68FFCC2F&iid=708DD6B15D2464E8&sid=B221F15A486F30C1&eid=8D0822DF60ACC08F&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=0&reference_num=0