We address the challenge of semantic gap reduction for image retrieval through an improved SVM-based active relevance feedback framework, together with a hybrid visual and concept...
This paper describes our novel retrieval model that is based on contexts of query terms in documents (i.e., document contexts). Our model is novel because it explicitly takes into...
Ho Chung Wu, Robert W. P. Luk, Kam-Fai Wong, K. L....
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 ...
Large search engines process thousands of queries per second over billions of documents, making query processing a major performance bottleneck. An important class of optimization...
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, rele...