Exploiting subclass information in Support Vector Machines

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2012, Pages 1076-1079

  Orfanidis, Georgios ^a   Tefas, Anastasios ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

DISCRIMINANT ANALYSIS; PATTERN RECOGNITION;

SUPPORT VECTOR MACHINES;

EID: 84874573390     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. E. Alpaydin. Combined 5 x 2 cv f test for comparing supervised classification learning algorithms. Neural Comput., 11: 1885-1892, November 1999.
2. X. Chen and T. Huang. Facial expression recognition: A clustering-based approach. Pattern Recognition Letters, 24: 1295-1302, 2003.
3. S. Escalera, D. Tax, O. Pujol, P. Radeva, and R. Duin. Subclass problem-dependent design of error-correcting output codes. IEEE Transactions in Pattern Analysis and Machine Intelligence, 30: 1041-1054, June 2008.
4. C. Feng, A. Sutherland, S. King, and S. Muggleton. Comparison of machine learning classifiers to statistics and neural networks. AI and Stats Conf., 1993.
5. T. S. Jaakkola and D. Haussler. Exploiting generative models in discriminative classifiers. Proceedings of the 1998 conference on Advances in neural information processing systems II, pages 487-493, 1999.
6. B. Leibe and B. Schiele. Analyzing appearance and contour based methods for object categorization. International Conference on Computer Vision and Pattern Recognition CVPR '03, June 2003.
7. P. Shivaswamy and T. Jebara. Relative margin machines. Neural Information Processing Systems, NIPS, 2008.
8. J. Siebert. Vehicle recognition using rule based methods. Turing Institute Research Memorandum TIRM-87-018, March 1987.
9. A. Tefas, C. Kotropoulos, and I. Pitas. Using support vector machines to enhance the performance of elastic graph matching for frontal face authentication. IEEE Trans. Pattern Anal. Mach. Intell., 23(7): 735-746, July 2001.
10. S. Theodoridis and K. Koutroumbas. Pattern Recognition. Academic Press, November 2008.
11. V. Vapnik. Statistical Learning Theory. Wiley, New York, NY, 1998.
12. S. Zafeiriou, A. Tefas, and I. Pitas. Minimum class variance support vector machines. IEEE Transaction on image processing, 10: 2551-2564, October 2007.
13. M. Zhu and A. M. Martinez. Subclass discriminant analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(8), August 2006.