Learning the semantics of images by using unlabeled samples

Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005

Volumn II, Issue , 2005, Pages 704-710

  Fan, Jianping ^a   Luo, Hangzai ^a   Gao, Yuli ^a  

^a University of North Carolina at Charlotte   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; HIERARCHICAL SYSTEMS; LEARNING SYSTEMS; MATHEMATICAL MODELS; PERSONNEL TRAINING; SEMANTICS;

ATOMIC IMAGE CONCEPTS; HIERARCHICAL CLASSIFIER TRAINING; HIGHER-LEVEL SEMANTIC IMAGE CONCEPTS; MULTI-LEVEL IMAGE CONCEPT MODELING;

IMAGE PROCESSING;

EID: 24644520645     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2005.207     Document Type: Conference Paper

References (18)

1. A.W.M. Smeulders, M. Worring, S. Santini, A. Gupta and R. Jain, "Content-based image retrieval at the end of the early years", IEEE Trans. on PAMI, vol.22, pp.1349-1380, 2000.
2. P. Lipson, E. Grimson, P. Sinha, "Configuration based scene classification and image indexing", CVPR, 1997.
3. J.S.D. Bonet and P. Viola, "A non-parametric multi-scale statistical model for natural images", NIPS, 1997.
4. K. Barnard and D. Forsyth, "Learning the semantics of words and pictures", ICCV, pp.408-415, 2001.
5. K. Branard, P. Duygulu, N. de Freitas, D. Forsyth. D. Blei, M.I. Jordan, "Matching words and pictures", Journal of Machine Learning Research, vol.3, pp.1107-1135, 2003.
6. S. Kumar and M. Hebert, "Man-made structure detection in natural images using a causal multiscale random field", CVPR, 2003.
7. C. Carson, S. Belongie, H. Greenspan, J. Malik, "Blobworld: Image segmentation using expectation-maximization and its application to image querying", IEEE Trans. PAMI, vol.24, no.8, 2002.
8. K. Nigam, A. McCallum, S. Thrun, T. Mitchell, "Text classification from labeled and unlabeled documents using EM", Machine Learning, vol.39, no.2, 2000.
9. F. Cozman, I. Cohen, "Unlabeled data can degrade classification performance of generative classifier", TR-HPL-2001-234, 2001.
10. M. Szummer and T. Jaakkola, "Information Regularization with Partially Labeled Data", NIPS, 2002.
11. M. Jordan, R. Jacobs, "Hierarchical mixtures of experts and the EM algorithm", Neural Computation, vol.6, 1994.
12. N. Vasconcelos and A. Lippman, "Learning mixture hierarchies", NIPS, 1999.
13. G. McLachlan and T. Krishnan, The EM algorithm and extensions, New York, John Wiley & Sons, 2000.
14. Y. Wu, Q. Tian, T.S. Huang, "Discriminant-EM algorithm with application to image retrieval", CVPR, 2000.
15. B. Zhang, C. Zhang, X. Yi, "Competitive EM algorithm for finite mixture models", Pattern Recognition, vol.37, 2004.
16. M. Figueiredo and A.K. Jain, "Unsupervised learning of finite mixture models", IEEE Trans. PAMI, vol.24, 2002.
17. A. McCallum, R. Rosenfeld, T. Mitchell, A.Y. Ng, "Improving text classification by shrinkage in a hierarchy of classes", ICML, 1998.
18. D. Koller and M. Sahami, "Hierarchically classifying documents using very few words", ICML, 1997.