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ISCIS
2009
Springer
14 years 2 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
MIR
2006
ACM
223views Multimedia» more  MIR 2006»
14 years 1 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose
PRL
2008
143views more  PRL 2008»
13 years 7 months ago
An active feedback framework for image retrieval
In recent years, relevance feedback has been studied extensively as a way to improve performance of content-based image retrieval (CBIR). Since users are usually unwilling to prov...
Tao Qin, Xu-Dong Zhang, Tie-Yan Liu, De-Sheng Wang...
ICCV
2011
IEEE
12 years 7 months ago
HEAT: Iterative Relevance Feedback with One Million Images
It has been shown repeatedly that iterative relevance feedback is a very efficient solution for content-based image retrieval. However, no existing system scales gracefully to hu...
Nicolae Suditu, Francois Fleuret
CVPR
2001
IEEE
14 years 9 months ago
Learning Similarity Measure for Natural Image Retrieval with Relevance Feedback
A new scheme of learning similarity measure is proposed for content-based image retrieval (CBIR). It learns a boundary that separates the images in the database into two parts. Im...
Guodong Guo, Anil K. Jain, Wei-Ying Ma, HongJiang ...