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2003
9 years 10 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»
10 years 1 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
MTA
2002
166views more  MTA 2002»
9 years 9 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
CVPR
2006
IEEE
10 years 11 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
SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
10 years 9 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
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