%0 Journal Article
%T Image Retrieval Based on Improved PSO Algorithm and Relevance Feedback<br>一种改进的粒子群算法和相关反馈的图像检索
%A TANG Zhao-xia
%A ZHANG Hui
%A XU Dong-mei
%A <br>唐朝霞
%A 章慧
%A 徐冬梅
%J 计算机科学
%D 2011
%I 
%X Because of semantic gap between low-level image features and high-level semantics, and user understanding image subj ectivity and variability, image retrieval results can not satisfy the needs of users. To solve this problem, PSO algorithm and relevance feedback were introduced into the image retrieval process,based on user feedback, W automatic adjustment and Beta adaptive mutation of PSO adjust the weights of the image feature dynamically, to improve search accuracy,better meet the needs of users.
%K Relevance feedback(RF)
%K Particle swarm optimization(PSO)
%K Image retrieval<br>相关反馈，粒子群算法，图像检索
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=17DDCED190714E79C6FDFAFB14A3449E&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=F3090AE9B60B7ED1&sid=B4E8EA49DAAEB84F&eid=5D8C08279A19B0D4&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0