A pyramidal neural network for visual pattern recognition

IEEE Transactions on Neural Networks

Volumn 18, Issue 2, 2007, Pages 329-343

  Phung, Son Lam ^a   Bouzerdoum, Abdesselam ^a  

^a UNIVERSITY OF WOLLONGONG   (Australia)

Author keywords

Gender classification; Neural network (NN); Pattern recognition; Pyramidal architecture; Receptive field; Training algorithms

Indexed keywords

BACKPROPAGATION; CONJUGATE GRADIENT METHOD; FACE RECOGNITION; FEATURE EXTRACTION; HIERARCHICAL SYSTEMS; MEAN SQUARE ERROR; SUPPORT VECTOR MACHINES;

DIMENSIONALITY REDUCTION; GENDER CLASSIFICATION; PYRAMIDAL NEURAL NETWORK; TRAINING ALGORITHMS;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BIOMETRY; COMPUTER ASSISTED DIAGNOSIS; FACE; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMETRY; FACE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 34047181683     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2006.884677     Document Type: Article

References (42)

1. K. Fukushima and N. Wake, "Handwritten alphanumeric character recognition by the neocognitron," IEEE Trans. Neural Netw., vol. 2, no. 3, pp. 355-365, Mar. 1991.
2. Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, "Gradient-based learning applied to document recognition," Proc. IEEE, vol. 86, no. 11, pp. 2278-2324, Nov. 1998.
3. M. D. Ganis, C. L. Wilson, and J. L. Blue, "Neural network-based systems for handprint OCR applications," IEEE Trans. Image Process., vol. 7, no. 8, pp. 1097-1112, Aug. 1998.
4. S. Yamaguchi and H. Itakura, "A car detection system using the neocognitron," in Proc. IEEE Int. Joint Conf. Neural Netw., 1991, vol. 2, pp. 1208-1213.
5. H. A. Rowley, S. Baluja, and T. Kanade, "Neural network-based face detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 1, pp. 23-38, Jan. 1998.
6. C. Garcia and M. Delakis, "Convolutional face finder: A neural architecture for fast and robust face detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 26, no. 11, pp. 1408-1423, Nov. 2004.
7. S. Lawrence, C. L. Giles, A. C. Tsoi, and A. D. Back, "Face recognition: A convolutional neural-network approach," IEEE Trans. Neural Netw., vol. 8, no. 1, pp. 98-113, Jan. 1997.
8. M. J. Er, W. Chen, and S. Wu, "High-speed face recognition based on discrete cosine transform and RBF neural networks," IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 679-691, May 2005.
9. M. Rosenblum, Y. Yacoob, and L. S. Davis, "Human expression recognition from motion using a radial basis function network architecture," IEEE Trans. Neural Netw., vol. 7, no. 5, pp. 1121-1138, Sep. 1996.
10. K. Fukushima, "Neocognitron: A hierarchical neural network capable of visual pattern recognition," Neural Netw., vol. 1, no. 2, pp. 119-130, 1988.
11. D. H. Hubel and T. N. Wiesel, "Receptive fields, binocular interaction and functional architecture," J. Physiol. - London, vol. 160, no. 1, pp. 106-154, 1962.
12. Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel, "Backpropagation applied to handwritten zip code recognition," Neural Comput., vol. 1, no. 4, pp. 541-551, 1989.
13. R. C. Gonzalez and R. E. Woods, Digital Image Pprocessing. Englewood Cliffs, NJ: Prentice-Hall, 2002.
14. F. Tivive and A. Bouzerdoum, "Efficient training algorithms for a class of shunting inhibitory convolutional neural networks," IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 541-556, May 2005.
15. M. Hoshino and J. Chao, "On representation and generalization capability of pyramid neural networks," in Proc. Int. Joint Conf. Neural Netw., 2002, vol. 2, pp. 1166-1171.
16. V. Cantoni and A. Petrosino, "Neural recognition in a pyramidal structure," IEEE Trans. Neural Netw., vol. 13, no. 2, pp. 472-480, Mar. 2002.
17. C. M. Bishop, Neural Networks For Pattern Recognition. Oxford, U.K.: Clarendon, 1996.
18. M. C. Joshi and K. M. Moudgalya, Optimization Theory and Practice. Harrow, U.K.: Alpha Science International Ltd., 2004.
19. J. S. Bridle, "Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition," in Neurocomputing: Algorithms, Architectures and Applications, F. Souli and J. Hrault, Eds. New York: Springer-Verlag, 1990, pp. 227-236.
20. E. K. P. Chong and S. H. Zak, An Introduction to Optimization. New York: Wiley, 1996.
21. S.-C. Ng, C.-C. Cheung, and S.-H. Leung, "Magnified gradient function with deterministic weight modification in adaptive learning," IEEE Trans. Neural Netw., vol. 15, no. 6, pp. 1411-1423, Nov. 2004.
22. N. Zhang, W. Wu, and G. Zheng, "Convergence of gradient method with momentum for two-layer feedforward neural networks," IEEE Trans. Neural Netw., vol. 17, no. 2, pp. 522-525, Mar. 2006.
23. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning internal representations by error propagation," in Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Cambridge, MA: Bradford Books, 1986, vol. I, pp. 318-362.
24. M. T. Hagan, H. B. Demuth, and M. H. Beale, Neural Network Design. Boston, MA: PWS-Kent, 1996.
25. M. Riedmiller and H. Braun, "A direct adaptive method of faster back-propagation learning: The RPROP algorithm," in Proc. IEEE Int. Conf. Neural Netw., San Francisco, CA, 1993, pp. 586-591.
26. M. T. Hagan and M. B. Menhaj, "Training feedforward networks with the Marquardt algorithm," IEEE Trans. Neural Netw., vol. 5, no. 6, pp. 989-993, Nov. 1994.
27. C. Charalambous, "A conjugate gradient algorithm for the efficient training of artificial neural networks," IEE Proc. Part G, vol. 139, no. 3, pp. 301-310, 1992.
28. M.-H. Yang, D. Kriegman, and N. Ahuja, "Detecting faces in images: A survey," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 1, pp. 34-58, Jan. 2002.
29. S. L. Phung, A. Bouzerdoum, and D. Chai, "Skin segmentation using color pixel classification: Analysis and comparison," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 1, pp. 148-154, Jan. 2005.
30. K. K. Sung and T. Poggio, "Example-based learning for view-based human face detection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 20, no. 1, pp. 39-51, Jan. 1998.
31. M.-H. Yang, D. Roth, and N. Ahuja, "A SNoW-based face detector," in Advances in Neural Information Processing Systems 12. Cambridge, MA: MIT Press, 2000, pp. 855-861.
32. S. Z. Li and A. K. Jain, Handbook of Face Recognition. New York: Springer-Verlag, 2005.
33. K. Ueki, H. Komatsu, S. Imaizumi, K. Kaneko, N. Sekine, J. Katto, and T. Kobayashi, "A method of gender classification by integrating facial, hairstyle, and clothing images," in Proc. Int. Conf. Pattern Recognit., 2004, vol. 4, pp. 446-449.
34. B. Golomb, D. T. Lawrence, and T. J. Sejnowski, "Sexnet: A neural network that identifies sex from human faces," Adv. Neural Inf. Process. Syst., vol. 3, pp. 572-577, 1991.
35. M. Gray, D. T. Lawrence, B. A. Golomb, and T. J. Sejnowski, "A perception revealing the face of sex," Neural Comput., vol. 7, no. 6, pp. 1160-1164, 1995.
36. S. Gutta, J. R. J. Huang, P. Jonathon, and H. Wechsler, "Mixture of experts for classification of gender, ethnic origin, and pose of human faces," IEEE Trans. Neural Netw., vol. 11, no. 4, pp. 948-960, Jul. 2000.
37. A. Jain and J. Huang, "Integrating independent components and linear discriminant analysis for gender classification," Proc. IEEE Int. Conf. Autom. Face Gesture Recognit., pp. 159-163, 2004.
38. B. Moghaddam and M.-H. Yang, "Learning gender with support faces," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 5, pp. 707-711, May 2002.
39. B. Wu, H. AI, and C. Huang, "Real-time gender classification," in Proc. SPIE Multi-Spectral Image Process. Pattern Recognit., Beijing, China, 2003, vol. 5286, pp. 498-503.
40. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," in Proc. Comput. Vis. Pattern Recognit., Kauai, Hawaii, 2001, pp. 511-518.
41. P. J. Phillips, H. Moon, S. A. Rizvi, and P. J. Rauss, "The FERET evaluation methodology for face-recognition algorithms," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 10, pp. 1090-1104, Oct. 2000.
42. C.-C. Chang and C.-J. Lin, LIBSVM: A library for support vector machines 2001 [Online]. Available: http://www.csie.ntu.edu.tw/cjlin/libsvm