In this paper, we study how to automatically exploit visual concepts in a text-based image retrieval task. First, we use Forest of Fuzzy Decision Trees (FFDTs) to automatically ann...
Sabrina Tollari, Marcin Detyniecki, Christophe Mar...
Performance of traditional content-based image retrieval systems is far from user’s expectation due to the ‘semantic gap’ between low-level visual features and the richness ...
In this paper we propose a new General Image DataBase (GIDB) model. The model establishes taxonomy based on the systematisation of existing approaches. The GIDB model is based on t...
Image retrieval based on content from digital libraries, multimedia databases, the Internet, and other sources has been an important problem addressed by several researchers. In t...
Image retrieval with relevance feedback suffers from the small sample problem. Recently, SVM active learning has been proposed to tackle this problem, showing promising results. H...