Robust support vector machine with bullet hole image classification

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews

Volumn 32, Issue 4, 2002, Pages 440-448

  Song, Qing ^a   Hu, Wenjie ^a   Xie, Wenfang ^b  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b CORETEC Incorporated ^*  (Canada)

Author keywords

Bullet hole classification; Robust support vector machine

Indexed keywords

ALGORITHMS; BOUNDARY CONDITIONS; CALCULATIONS; DECISION THEORY; ERROR ANALYSIS; IMAGE ANALYSIS; OPTIMIZATION; PATTERN RECOGNITION; PROBLEM SOLVING;

BULLET HOLE IMAGE CLASSIFICATION; SUPPORT VECTOR MACHINE;

NEURAL NETWORKS;

EID: 0036881508     PISSN: 10946977     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCC.2002.807277     Document Type: Article

References (14)

1. V.N. Vapnik, Statistical Learning Theory. New York: Wiley, 1998.
2. B. E. Boser, I. M. Guyon, and V. N. Vapnik, "A training algorithm for optimal margin classifier," in Proc. 5th ACM Workshop Comput. Learning Theory, Pittsburgh, PA, July 1992, pp. 144-152.
3. C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Data Mining Knowl. Discovery, vol. 2, no. 2, pp. 121-167, 1998.
4. E. E. Osuna, R. Freund, and F. Girosi, "Support vector machines: training and application," MIT A.I. Lab., A.I. Memo 1602, 1997.
5. ____, "Training support vector machines: An application to face dectection," in Proc. Computer Vision Pattern Recognit., 1997, pp. 130-136.
6. A. K. Jain, Fundamentals of Digital Image Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989.
7. M. Oren, C. Papageorgious, P. Sinha, E. Osuna, and T. Poggio, "Pedestrian detection using wavelet templates," in Proc. Computer Vision and Pattern Recognition, 1997, pp. 193-199.
8. T. Joachims. (1997) Text categorization with support vector machines. Univ. Dortmund, Dortmund, Germany. [Online]. Available: ftp:/ftp-ai.informatik.uni-dortmund.de/pub/Reports/report23.ps.gz
9. I. Guyon, N. Matic, and V.N. Vapnik et al., "Discovering informative patterns and data cleaning," in Advances in Knowledge Discovery and Data Mining, U. M. Fayyad et al., Eds. Cambridge, MA: MIT Press, 1996, pp. 181-203.
10. X. G. Zhang, "Using class-center vectors to build support vector machines," presented at the IEEE Proc. Neural Net. Signal Processing IX, Aug. 1999.
11. R. Herbrich and J. Weston, "Adaptive margin support vector machines for classification," in Proc. 9th ICANN, vol. 2, Sept. 1999, pp. 880-885.
12. S. Haykin, "Neural networks-A comprehensive Foundation," in Chapter 6-Support Vector Machine. Englewood Cliffs, NJ: Prentice-Hall, 1999.
13. W. F. Xie, D. J. Hou, and Q. Song, "Bullet-hole image classification with support vector machines," presented at the IEEE Workshop Neural Networks Signal Processing, Australia, Dec. 2000.
14. S. Gunn, "Support vector machines for classification and regression," Univ. Southampton, Southampton, U.K., ISIS Tech. Rep., May 1998. Image Speech and Intelligent Systems Group.