Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. In this paper, we propose an approach based on On...
Chengcui Zhang, Xin Chen, Min Chen, Shu-Ching Chen...
Active learning methods aim to select the most informative unlabeled instances to label first, and can help to focus image or video annotations on the examples that will most impr...
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...
Learning-enhanced relevance feedback is one of the most promising and active research directions in recent year's content-based image retrieval. However, the existing approac...
Image retrieval has become an interesting and active field due to the increasing necessity of searching and browsing very large image repositories. Images are represented using s...