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ICMCS
2000
IEEE
170views Multimedia» more  ICMCS 2000»
13 years 9 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
ISCIS
2009
Springer
13 years 12 months ago
Dynamic feature weights with relevance feedback in content-based image retrieval
— In this paper, we present a novel relevance feedback method for Content-Based Image Retrieval systems based on dynamic feature weights. The proposed method utilizes intracluste...
Esin Guldogan, Moncef Gabbouj
VIP
2003
13 years 6 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
CIVR
2005
Springer
137views Image Analysis» more  CIVR 2005»
13 years 11 months ago
Aspect-Based Relevance Learning for Image Retrieval
We analyze the special structure of the relevance feedback learning problem, focusing particularly on the effects of image selection by partial relevance on the clustering behavio...
Mark J. Huiskes
ISCI
2008
86views more  ISCI 2008»
13 years 5 months ago
Image retrieval model based on weighted visual features determined by relevance feedback
Woo-Cheol Kim, Ji-Young Song, Seung-Woo Kim, Sangh...