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ICTIR
2009
Springer
14 years 2 months ago
A Four-Factor User Interaction Model for Content-Based Image Retrieval
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...
JMLR
2010
141views more  JMLR 2010»
13 years 2 months ago
Pinview: Implicit Feedback in Content-Based Image Retrieval
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...
JUCS
2002
231views more  JUCS 2002»
13 years 7 months ago
Efficient Content-Based and Metadata Retrieval in Image Database
: Managing image data in a database system using metadata has been practiced since the last two decades. However, describing an image fully and adequately with metadata is practica...
Solomon Atnafu, Richard Chbeir, Lionel Brunie
ICIP
2010
IEEE
13 years 5 months ago
Image retrieval with feature selection and relevance feedback
This paper proposes a new content based image retrieval (CBIR) system combined with relevance feedback and the online feature selection procedures. A measure of inconsistency from...
Yu Sun, Bir Bhanu
ICCV
2007
IEEE
14 years 9 months ago
Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval
Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of quest...
Hichem Sahbi, Jean-Yves Audibert, Renaud Keriven