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VISUAL
1999
Springer
13 years 11 months ago
Relevance Feedback and Term Weighting Schemes for Content-Based Image Retrieval
This paper describes the application of techniques derived from text retrieval research to the content-based querying of image databases. Speci cally, the use of inverted les, fre...
David Squire, Wolfgang Müller 0002, Henning M...
ICMCS
2005
IEEE
134views Multimedia» more  ICMCS 2005»
14 years 1 months ago
Relevance Feedback Methods in Content Based Retrieval and Video Summarization
In the current state-of-the-art in multimedia content analysis (MCA), the fundamental techniques are typically derived from core pattern recognition and computer vision algorithms...
Micha Haas, Ard Oerlemans, Michael S. Lew
SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
14 years 7 months ago
Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Deok-Hwan Kim, Chin-Wan Chung
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...
MTA
2002
166views more  MTA 2002»
13 years 7 months ago
MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback
ThefieldofContent-BasedVisualInformationRetrieval(CBVIR)hasexperiencedtremendousgrowth in the recent years and many research groups are currently working on solutions to the proble...
Oge Marques, Borko Furht