In the current state-of-the-art in multimedia content analysis (MCA), the fundamental techniques are typically derived from core pattern recognition and computer vision algorithms...
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
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 has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...
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...