Image databases are nowadays widely exploited in a number of different contexts, ranging from history of art, through medicine, to education. Existing querying paradigms are based ...
This paper introduces a composite learning approach for image retrieval with relevance feedback. The proposed system combines the radial basis function (RBF) based lowlevel learni...
Motivated by the need to efficiently leverage user relevance feedback in content-based retrieval from image databases, we propose a fast, clustering-based indexing technique for e...
With Internet delivery of video content surging to an unprecedented level, video recommendation has become a very popular online service. The capability of recommending relevant v...
Bo Yang, Tao Mei, Xian-Sheng Hua, Linjun Yang, Shi...
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...