This paper presents a Bayesian Network model for ContentBased Image Retrieval (CBIR). In the explanation and test of this work, only two images features (semantic evidences) are i...
Paulo S. Rodrigues, Gilson A. Giraldi, Ade A. Arau...
In content-based image retrieval, relevance feedback has been introduced to narrow the gap between low-level image feature and high-level semantic concept. Furthermore, to speed u...
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...