In this paper, we propose an image semantic model based on the knowledge and criteria in the field of linguistics and taxonomy. Our work bridges the "semantic gap" by sea...
Xiaoyan Li, Lidan Shou, Gang Chen, Tianlei Hu, Jin...
Abstract. Content-based image search has long been considered a difficult task. Making correct conjectures on the user intention (perception) based on the query images is a critica...
In order to store, and retrieve images from large databases, we propose a framework, based on multiple description coding paradigm, that disseminates images over distributed serve...
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
As large quantity of document images is getting archived by the digital libraries, there is a need for an efficient search strategies to make them available as per users informatio...