In this paper, we present a long term learning system for content based image retrieval over a network. Relevant feedback is used among different sessions to learn both the simila...
Relevance feedback (RF) has been extensively studied in the content-based image retrieval community. However, no commercial Web image search engines support RF because of scalabil...
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Content Based Image Retrieval (CBIR) has become one of the most active research areas in computer science. Relevance feedback is often used in CBIR systems to bridge the semantic ...
Lijun Zhang, Chun Chen, Wei Chen, Jiajun Bu, Deng ...
Content-Based Image Retrieval (CBIR) is one of the most active research areas in recent years. Many visual feature representations have been explored and many systems built. Howev...