In recent years, relevance feedback has been studied extensively as a way to improve performance of content-based image retrieval (CBIR). Since users are usually unwilling to prov...
Tao Qin, Xu-Dong Zhang, Tie-Yan Liu, De-Sheng Wang...
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
Aspect-based relevance learning is a relevance feedback scheme based on a natural model of relevance in terms of image aspects. In this paper we propose a number of active learning...
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...
Active learning is a framework that has attracted a lot of research interest in the content-based image retrieval (CBIR) in recent years. To be effective, an active learning syste...