In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
This paper represents the first participation of the Institute of Statistical Studies and Research at Cairo University group in CLEF 2009-Medical image retrieval track. Our system...
Recent advances in processing and networking capabilities of computers have led to an accumulation of immense amounts of multimedia data such as images. One of the largest reposit...
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...