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...
A novel indexing and access method, called Affinity Hybrid Tree (AH-Tree), is proposed to organize large image data sets efficiently and to support popular image access mechanisms...
A combination of several classifiers using global features for the content description of medical images is proposed. Beside well known texture histogram features, downscaled repr...
This paper conducts an empirical evaluation of MPEG-7 visual part of experimentation model (XM) color descriptors in a challenging problem of content-based retrieval of semantic i...
Image databases are nowadays widely exploited in a number of different contexts, ranging from history of art, through medicine, to education. Existing querying paradigms are based ...