In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques i...
Haiming Liu 0002, Victoria S. Uren, Dawei Song, St...
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
This paper presents a novel visual approach to evaluate, in a fast and effective way, the development of new image feature extraction techniques concerning content-based image ret...
A novel indexing and access method, called Affinity Hybrid Tree (AH-Tree), is proposed to organize large image data sets efficiently and to support popular image access mechanisms...
Content-Based Image Retrieval (CBIR) has become one of the most active research areas in the past few years. Many visual feature representations have been explored and many system...