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VLC
2008
178views more  VLC 2008»
13 years 7 months ago
An exploration of diversified user strategies for image retrieval with relevance feedback
Given the difficulty of setting up large-scale experiments with real users, the comparison of content-based image retrieval methods using relevance feedback usually relies on the ...
Michel Crucianu, Jean-Philippe Tarel, Marin Fereca...
MMM
2005
Springer
117views Multimedia» more  MMM 2005»
14 years 1 months ago
Subspace Clustering and Label Propagation for Active Feedback in Image Retrieval
In recent years, relevance feedback has been studied extensively as a way to improve performance of content-based image retrieval (CBIR). However, since users are usually unwillin...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, Wei-Ying Ma, ...
CVPR
2008
IEEE
14 years 9 months ago
Semi-supervised distance metric learning for Collaborative Image Retrieval
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, rele...
Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
CIVR
2006
Springer
181views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Image Searching and Browsing by Active Aspect-Based Relevance Learning
Aspect-based relevance learning is a relevance feedback scheme based on a natural model of relevance in terms of image aspects. In this paper we propose a number of active learning...
Mark J. Huiskes
CISST
2004
164views Hardware» more  CISST 2004»
13 years 9 months ago
Probabilistic Region Relevance Learning for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective method for adaptively computing local feature relevance in content-based image retrieval. It computes flexible retr...
Iker Gondra, Douglas R. Heisterkamp