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VIP
2003
13 years 5 months ago
Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network
Relevance feedback is a powerful query modification technique in the field of content-based image retrieval. The key issue in relevance feedback is how to effectively utilize the ...
Jing Xin, Jesse S. Jin
ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
13 years 8 months ago
Update Relevant Image Weights for Content-Based Image Retrieval using Support Vector Machines
Relevance feedback [1] has been a powerful tool for interactive Content-Based Image Retrieval (CBIR). During the retrieval process, the user selects the most relevant images and p...
Qi Tian, Pengyu Hong, Thomas S. Huang
CVPR
2006
IEEE
14 years 6 months ago
A Simple Bayesian Framework for Content-Based Image Retrieval
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
Katherine A. Heller, Zoubin Ghahramani
MTA
2002
166views more  MTA 2002»
13 years 4 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
VISUAL
2000
Springer
13 years 7 months ago
Content-Based Image Retrieval by Relevance Feedback
Relevance feedback is a powerful technique for content-based image retrieval. Many parameter estimation approaches have been proposed for relevance feedback. However, most of them ...
Zhong Jin, Irwin King, Xuequn Li