Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
This paper describes Pinview, a content-based image retrieval system that exploits implicit relevance feedback during a search session. Pinview contains several novel methods that...
Peter Auer, Zakria Hussain, Samuel Kaski, Arto Kla...
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...
: Despite the efforts to reduce the semantic gap between user perception of similarity and featurebased representation of images, user interaction is essential to improve retrieval...
Abstract. In this paper, the Ssair (Semi-Supervised Active Image Retrieval) approach, which attempts to exploit unlabeled data to improve the performance of content-based image ret...