Relevance feedback in content-based image retrieval: Some recent advances

Information Sciences

Volumn 148, Issue 1-4, 2002, Pages 129-137

  Zhou, Xiang Sean ^a   Huang, Thomas S ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FEEDBACK; PROBABILITY; SEMANTICS;

FEEDBACK ALGORITHMS;

CONTENT BASED RETRIEVAL;

EID: 0036891833     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0020-0255(02)00286-4     Document Type: Article

References (9)

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3. Zhou X.S., Huang T.S. Small sample learning during multimedia retrieval using BiasMap. proceedings of the International Conference on Computer Vision and Pattern Recognition. Hawaii. 2001.
4. Barnard K., Forsyth D.A. Learning the semantics of words and pictures. International Conference on Computer Vision. Vancouver. 2001.
5. Zhou X.S., Huang T.S. Unifying keywords and contents for image retrieval. International Workshop on Content-Based Multimedia Indexing. Italy. 2001.
6. Vapnik V. The Nature of Statistical Learning Theory. 1995;Springer, New York.
7. Minka S.et al. Fisher discriminant analysis with kernels. Proceedings of the IEEE workshop on Neural Networks for Signal Processing. 1999.
8. X.S. Zhou, T.S. Huang, Edge-based structural features for content-based image retrieval, Pattern Recognition Lett. 22 (2001) 457-468.
9. Y. Rui, T.S. Huang, Optimizing learning in image retrieval: in proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. South Carolina. June 2000.