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...
The problem of content based image retrieval (CBIR) has traditionally been investigated within a framework that emphasises the explicit formulation of a query: users initiate an au...
In this paper, a non-linear relevance feedback mechanism is proposed for increasing the performance and the reliability of content-based retrieval systems. In particular, the huma...
Nikolaos D. Doulamis, Anastasios D. Doulamis, Stef...
Today's Content-Based Image Retrieval (CBIR) techniques are based on the "k-nearest neighbors" (kNN) model. They retrieve images from a single neighborhood using lo...
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...