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...
The performance of a content based image retrieval (CBIR) system is inherently constrained by the features adopted to represent the images in the database. In this paper, a new ap...
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...
Content Based Image Retrieval (CBIR) has become one of the most active research areas in computer science. Relevance feedback is often used in CBIR systems to bridge the semantic ...
Lijun Zhang, Chun Chen, Wei Chen, Jiajun Bu, Deng ...
Feature extraction and selection are two important steps for shape retrieval. Given a data set, a set of features which describe the shape property from different aspects are extr...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...