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...
This paper presents a new approach to ranking relevant images for retrieval. Distance in the feature space associated with a kernel is used to rank relevant images. An adaptive qu...
The majority of today's content based image retrieval systems rely on low-level image descriptors which limit their capability to support meaningful interactions with the use...
For almost a decade, Content-Based Image Retrieval has been an active research area, yet one fundamental problem remains largely unsolved: how to measure perceptual similarity. To...
Content-based Image retrieval has become an important part of information retrieval technology. Images can be viewed as high dimensional data and are usually represented by their ...
Ying Liu, Xin Chen, Chengcui Zhang, Alan P. Spragu...