Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
In this paper, we present a long term learning system for content based image retrieval over a network. Relevant feedback is used among different sessions to learn both the simila...
Feature histograms based on the evaluation of Haar integrals with nonlinear kernel functions were used successfully for the purpose of invariant content based image retrieval. In ...
We describe our experiments for the Image CLEF medical retrieval task. Our efforts were focused on the initial visual search. A content based approach was followed. We used textur...
Peter Howarth, Alexei Yavlinsky, Daniel Heesch, St...
Abstract. Content-based image retrieval (CBIR) with global features is notoriously noisy, especially for image queries with low percentages of relevant images in a collection. More...
Avi Arampatzis, Konstantinos Zagoris, Savvas A. Ch...