In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
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...
In relevance feedback algorithms, selective sampling is often used to reduce the cost of labeling and explore the unlabeled data. In this paper, we proposed an active learning alg...
We have proposed a novel image retrieval system that incorporates a workspace where users can organise their search results. A task-oriented and usercentred experiment has been dev...
In this paper, an image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segme...
Vasileios Mezaris, Ioannis Kompatsiaris, Michael G...