This paper introduces a composite learning approach for image retrieval with relevance feedback. The proposed system combines the radial basis function (RBF) based lowlevel learni...
Relevance feedback has been an indispensable component for multimedia retrieval systems. In this paper, we present an adaptive pattern discovery method, which addresses relevance ...
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...
In this paper, we propose adaptive multiple feedback strategies for interactive video retrieval. We first segregate interactive feedback into 3 distinct types (recall-driven relev...
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...