This paper introduces a composite learning approach for image retrieval with relevance feedback. The proposed system combines the radial basis function (RBF) based lowlevel learni...
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...
This paper describes an approach to optimize query by visual example results, by combining visual features and implicit user feedback in interactive video retrieval. To this end, ...
Stefanos Vrochidis, Ioannis Kompatsiaris, Ioannis ...
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
This paper presents an effective fuzzy long-term semantic learning method for relevance feedback-based image retrieval. The proposed system uses a statistical correlationbased met...