In recent years, relevance feedback has been studied extensively as a way to improve performance of content-based image retrieval (CBIR). Since users are usually unwilling to prov...
Tao Qin, Xu-Dong Zhang, Tie-Yan Liu, De-Sheng Wang...
Content-based image retrieval (CBIR) is a group of techniques that analyzes the visual features (such as color, shape, texture) of an example image or image subregion to find simi...
We propose a new “content-free” image retrieval method which attempts to exploit certain common tendencies that exist among people’s interpretation of images from user feedb...
Conventional approaches to image retrieval are based on the assumption that relevant images are physically near the query image in some feature space. This is the basis of the clu...
Relevance feedback has been proposed as an important technique to boost the retrieval performance in content-based image retrieval (CBIR). However, since there exists a semantic g...