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| A Parallel Framework For Multilayer Perceptron For Human Face Recognition
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Source |
International Journal of Computer Science and Security (IJCSS) |
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Table of Contents |
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Volume: 3 Issue: 6 |
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Pages: 448-594 |
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Publication
Date: January 2010 |
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ISSN
(Online): 1985-1553 |
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491 - 507 |
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Author(s) |
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Published
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31-01-2010 |
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Publisher |
CSC
Journals, Kuala Lumpur,
Malaysia |
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ADDITIONAL
INFORMATION |
| Keywords Abstract References Cited by Related Articles Collaborative
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KEYWORDS: Artificial Neural Network, Network architecture, All-Class-in-One-Network (ACON), One-Class-in-One-Network (OCON), PCA, Multilayer Perceptron and Face recognition |
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| Artificial neural networks have already shown their success in face recognition and similar complex pattern recognition tasks. However, a major disadvantage of the technique is that it is extremely slow during training for larger classes and hence not suitable for real-time complex problems such as pattern recognition. This is an attempt to develop a parallel framework for the training algorithm of a perceptron. In this paper, two general architectures for a Multilayer Perceptron (MLP) have been demonstrated. The first architecture is All-Class-in-One-Network (ACON) where all the classes are placed in a single network and the second one is One-Class-in-One-Network (OCON) where an individual single network is responsible for each and every class. Capabilities of these two architectures were compared and verified in solving human face recognition, which is a complex pattern recognition task where several factors affect the recognition performance like pose variations, facial expression changes, occlusions, and most importantly illumination changes. Experimental results show that the proposed OCON structure performs better than the conventional ACON in terms of network training convergence speed and which can be easily exercised in a parallel environment. |
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| 1 |
M. K. Bhowmik, ”Artificial Neural Network as a Soft Computing Tool – A case study”, In Proceedings of National Seminar on Fuzzy Math. & its application, Tripura University, November 25 – 26, 2006, pp: 31 – 46.
|
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|
| 2 |
M. K. Bhowmik, D. Bhattacharjee and M. Nasipuri, “Topological Change in Artificial Neural Network for Human Face Recognition”, In Proceedings of National Seminar on Recent Development in Mathematics and its Application, Tripura University, November 14 – 15, 2008, pp: 43 – 49.
|
|
|
| 3 |
I. Aleksander and H. Morton, “An introduction to Neural Computing,” Chapman & Hall, London, 1990.
|
|
|
| 4 |
R. Hecht-Nielsen, “Neurocomputing,” Addison-Wesley, 1990.
|
|
|
| 5 |
M. Turk and A. Pentland, “Eigenfaces for recognition”, Journal of Cognitive Neuro-science, March 1991. Vol. 3, No-1, pp. 71-86.
|
|
|
| 6 |
L. Sirovich and M. Kirby, “A low-dimensional procedure for the characterization of human faces,” J. Opt. Soc. Amer. A 4(3), pp. 519-524, 1987.
|
|
|
| 7 |
A. S. Georghiades, P. N. Belhumeur and D. J. Kriegnab, “From Few to Many: Illumination Cone Models for face Recognition under Variable Lighting and Pose”, IEEE Trans. Pattern Anal. Mach. Intelligence, 2001, vol. 23, No. 6, pp. 643 – 660.
|
|
|
| 8 |
D. Bhattacharjee, “Exploiting the potential of computer network to implement neural network in solving complex problem like human face recognition,” Proc. of national Conference on Networking of Machines, Microprocessors, IT, and HRD-need of the nation in the next millennium, Kalyani Engg. College, Kalyani, West Bengal, 1999.
|
|
|
| 9 |
Pradeep K. Sinha, “Distributed Operating Systems-Concepts and Design,” PHI, 1998. [8] M. K. Bhowmik, D. Bhattacharjee, M. Nasipuri, D. K. Basu and M. Kundu; “Classification of Fused Face Images using Multilayer Perceptron Neural Network”, proceeding of International Conference on Rough sets, Fuzzy sets and Soft Computing, Nov 5–7, 2009, organized by Department of Mathematics, Tripura University pp. 289-300.
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M.K. Bhowmik, D. Bhattacharjee, M. Nasipuri, D.K. Basu and M. Kundu, “Classification of Polar-Thermal Eigenfaces using Multilayer Perceptron for Human Face Recognition”, proceedings of the 3rd IEEE Conference on Industrial and Information Systems (ICIIS-2008), IIT Kharagpur, India, Dec 8-10, 2008, pp. 118.
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M.K. Bhowmik, D. Bhattacharjee, M. Nasipuri, D.K. Basu and M. Kundu, “Classification of Log-Polar-Visual Eigenfaces using Multilayer Perceptron for Human Face Recognition”, proceedings of The 2nd International Conference on Soft computing (ICSC-2008), IET, Alwar, Rajasthan, India, Nov 8–10, 2008, pp.107-123.
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| 12 |
M.K. Bhowmik, D. Bhattacharjee, M. Nasipuri, D.K. Basu and M. Kundu, “Human Face Recognition using Line Features”, proceedings of National Seminar on Recent Advances on Information Technology (RAIT-2009), Indian School of Mines University, Dhanbad, Feb 6- 7,2009, pp. 385-392.
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| 13 |
P. Raviram, R.S.D. Wahidabanu Implementation of artificial neural network in concurrency control of computer integrated manufacturing (CIM) database, International Journal of Computer Science and Security (IJCSS), Volume 2, Issue 5, pp. 23-25, September/October 2008.
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| 14 |
Teddy Mantoro, Media A. Ayu, “Toward The Recognition Of User Activity Based On User Location In Ubiquitous Computing Environments,” International Journal of Computer Science and Security (IJCSS)Volume 2, Issue 3, pp. 1-17, May/June 2008.
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| 15 |
Sambasiva Rao Baragada, S. Ramakrishna, M.S. Rao, S. Purushothaman , “Implementation of Radial Basis Function Neural Network for Image Steganalysis,” International Journal of Computer Science and Security (IJCSS) Volume 2, Issue 1, pp. 12-22, January/February 2008.
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N. Belghini, A. Zarghili, J. Kharroubi and A. Majda, , “A Color Facial Authentification System Based On Semi Supervised Backporpagation Neural Network”, in Proceedings, Multimedia Computing and Systems (ICMCS), 2011 International Conference , Ouarzazate, 7-9 April 2011, pp. 1-4.
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M. K. Bhowmik , D. Bhattacharjee , M. Nasipuri , D. K. Basu and M. Kundu, “Fusion of Wavelet Coefficients from Visual and Thermal Face Images for Human Face Recognition – A Comparative Study”, International Journal of Image Processing (IJIP), 4(1), pp. 12 – 23, 2010.
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TechRepublic
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arxiv.org
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Universität Trier
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The SAO/NASA Astrophysics Data System
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Q-Sensei Corp
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eprintweb.org
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math-arch
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Tripura University
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The SCEAS System
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| Mrinal Kanti Bhowmik : Colleagues
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| Debotosh Bhattacharjee : Colleagues
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| Mita Nasipuri : Colleagues
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| Dipak Kumar Basu : Colleagues
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| Mahantapas Kundu : Colleagues
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