Large amount of images need an efficient way of retrieving them. The usual approach of manually annotating images and/or providing a syntactic retrieval capability lacks flexibi...
This paper presents a framework for building rule-based image retrieval (RBIR) systems. Soft computing based multimedia data mining techniques are employed to extract and optimize...
In recent years, content-based image retrieval has become more and more important in many application areas. Similarity retrieval is inherently a very demanding process, in partic...
Relevance feedback (RF) has been an active research area in Content-based Image Retrieval (CBIR). RF intends to bridge the gap between the low-level image features and the high-le...
Xiaoqian Xu, D. J. Lee, Sameer Antani, L. Rodney L...
Relevance feedback is the state-of-the-art approach for adjusting query results to the needs of the users. This work extends the existing framework of image retrieval with relevan...
Euripides G. M. Petrakis, Klaydios Kontis, Epimeni...
In this paper, we draw an analogy between image retrieval and text retrieval and propose a visual phrase-based approach to retrieve images containing desired objects. The visual p...
Relevance feedback (RF) has been extensively studied in the content-based image retrieval community. However, no commercial Web image search engines support RF because of scalabil...
Relevance feedback (RF) and region-based image retrieval (RBIR) are two widely used methods to enhance the performance of contentbased image retrieval (CBIR) systems. In this paper...
Abstract— This demonstration highlights the benefits that image retrieval systems can enjoy by use of a thoughtful interface. We present a live demonstration of PRISM, a new Web...
Liam M. Mayron, Oge Marques, Gustavo B. Borba, Hum...
To bridge the gap between high level semantic concepts and low level visual features in content-based image retrieval (CBIR), online feature selection is really required. An effec...