Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructe...
Experiential image retrieval systems aim to provide the user with a natural and intuitive search experience. The goal is to empower the user to navigate large collections based on...
Bart Thomee, Mark J. Huiskes, Erwin M. Bakker, Mic...
In this paper, an interactive image retrieval scheme using MPEG-7 visual descriptors is proposed. The performance of image retrieval systems is still limited due to semantic gap, w...
We introduce the problem of repetitive nearest neighbor search in relevance feedback and propose an efficient search scheme for high dimensional feature spaces. Relevance feedback...