We address the challenge of semantic gap reduction for image retrieval through an improved SVM-based active relevance feedback framework, together with a hybrid visual and concept...
In this paper we predict the relevance of images based on a lowdimensional feature space found using several users’ eye movements. Each user is given an image-based search task,...
Zakria Hussain, Kitsuchart Pasupa, John Shawe-Tayl...
Content-based image retrieval methods based on the Euclidean metric expect the feature space to be isotropic. They suer from unequal dierential relevance of features in comput...
This paper represents the first participation of the Institute of Statistical Studies and Research at Cairo University group in CLEF 2009-Medical image retrieval track. Our system...
Inaccurate or ambiguous expressions in queries lead to poor results in information retrieval. We assume that iterative user feedback can improve the quality of queries. To this end...
Maher Ben Moussa, Marco Pasch, Djoerd Hiemstra, Pa...