Applications of multi-objective structure optimization

Neurocomputing

Volumn 69, Issue 7-9 SPEC. ISS., 2006, Pages 701-713

  Gepperth, Alexander ^a   Roth, Stefan ^a  

^a RUHR UNIVERSITY BOCHUM   (Germany)

Author keywords

Classification; Evolutionary algorithms; Multi objective optimization; Multilayer perceptrons; NN pruning; NN structure optimization

Indexed keywords

EMBEDDED SYSTEMS; EVOLUTIONARY ALGORITHMS; HEURISTIC METHODS; MULTILAYER NEURAL NETWORKS; OPTIMIZATION;

FEED-FORWARD NEURAL NETWORKS; MULTI-OBJECTIVE OPTIMIZATION; NEURAL NETWORK PRUNING; NEURAL NETWORK STRUCTURE OPTIMIZATION; OPTIMIZATION HEURISTIC;

FEEDFORWARD NEURAL NETWORKS;

ACCURACY; ALGORITHM; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER PROGRAM; EMBEDDING; IMAGE PROCESSING; INFORMATION PROCESSING; INTERMETHOD COMPARISON; MATHEMATICAL COMPUTING; MENTAL TASK; ONLINE SYSTEM; POSITIVE FEEDBACK; PRIORITY JOURNAL; PROBABILITY; PROCESS OPTIMIZATION; STATISTICAL SIGNIFICANCE;

EID: 32544440460     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2005.12.017     Document Type: Article

References (51)

1. H.A. Abbass Speeding up backpropagation using multiobjective evolutionary algorithms Neural Comput. 15 11 2003 2705-2726
2. C. Bahlmann Y. Zhu V. Ramesh M. Pellkofer T. Koehler A system for traffic sign detection, tracking, and recognition using color, shape and motion information in: Proceedings of the IEEE Symposium on Intelligent Vehicles 2005 255-260
3. P.L. Bartlett The sample complexity of pattern classification with neural networks: The size of the weights is more important than the size of the network IEEE Trans. Inform. Theory 44 2 1998 525-536
4. H. Braun Neurale Netze: Optimierung durch Lernen und Evolution 1997 Springer Berlin
5. T. Bücher C. Curio H. Edelbrunner C. Igel D. Kastrup I. Leefken G. Lorenz A. Steinhage W. von Seelen Image processing and behaviour planning for intelligent vehicles IEEE Trans. Industrial Electron. 90 1 2003 62-75
6. R. Caruana S. Lawrence C.L. Giles Overfitting in neural networks: backpropagation, conjugate gradient, and early stopping Advances in Neural Information Processing Systems vol. 13 2001 MIT Press Cambridge, MA 402-408
7. M. Chun J. Wolfe Visual attention E. Goldstein Blackwell's Handbook of Perception 2001 Blackwell Oxford, UK 272-310
8. C. Coello Coello D. Van Veldhuizen G. Lamont Evolutionary Algorithms for Solving Multi-objective Problems 2002 Kluwer Academic Publishers New York
9. L. Davis Adapting operator probabilities in genetic algorithms J.D. Schaffer Proceedings of the Third International Conference on Genetic Algorithms, ICGA'89 1989 Morgan Kaufmann Los Altos, CA 61-69
10. K. Deb Multi-objective Optimization using Evolutionary Algorithms 2001 Wiley New York
11. K. Deb S. Agrawal A. Pratap T. Meyarivan A fast and elitist multiobjective genetic algorithm: NSGA-II IEEE Trans. Evol. Comput. 6 2 2002 182-197
12. E. Dickmanns B. Mysliwetz Recursive 3-D road and relative ego-state recognition IEEE Trans. Pattern Anal. Mach. Intell. 14 2 1992 199-213
13. A.E. Eiben R. Hinterding Z. Michalewicz Parameter control in evolutionary algorithms IEEE Trans. Evol. Comput. 3 2 1999 124-141
14. J.E. Fieldsend S. Singh Pareto evolutionary neural networks IEEE Trans. Neural Networks 16 2 2005 338-354
15. D.B. Fogel Evolutionary Computation: Toward a New Philosophy of Machine Intelligence 1995 IEEE Press Piscataway, NJ, USA
16. N. Garcia-Pedrajas C. Hervas-Martinez J. Munos-Perez Multi-objective cooperative coevolution of artificial neural networks (multi-objective cooperative networks) Neural Networks 15 2002 1259-1278
17. A. Gepperth J. Edelbrunner T. Bücher Real-time detection and classification of cars in video sequences in: Proceedings of the IEEE Symposium on Intelligent Vehicles 2005 625-631
18. J. Gonzalez I. Rojas J. Ortega H. Pomares J. Fernandez A. Diaz Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation IEEE Trans. Neural Networks 14 6 2003 1478-1495
19. E. Hjelmas B.K. Low Face detection: A survey Comput. Vision and Image Understanding 83 2001 236-274
20. H.M. Hunke, Locating and tracking of human faces with neural networks, Master's Thesis, University of Karlsruhe, Germany, 1994.
21. M. Hüsken, M. Brauckmann, S. Gehlen, K. Okada, C. von der Malsburg, Evaluation of implicit 3D modeling for pose invariant face recognition, in: A.K. Jain, N.K. Ratha (Eds.), Defense and Security Symposium 2004: Biometric Technology for Human Identification, Proceedings of SPIE, vol. 5404, The International Society for Optical Engineering, 2004.
22. C. Igel M. Hüsken Empirical evaluation of the improved Rprop learning algorithm Neurocomput. 50 C 2003 105-123
23. C. Igel M. Kreutz Operator adaptation in evolutionary computation and its application to structure optimization of neural networks Neurocomput. 55 1-2 2003 347-361
24. C. Igel B. Sendhoff Synergies between evolutionary and neural computation M. Verleysen 13th European Symposium on Artificial Neural Networks (ESANN 2005) 2005 241-252
25. C. Igel, S. Wiegand, F. Friedrichs, Evolutionary optimization of neural systems: The use of self-adptation, in: M.G. de Bruin, D.H. Mache, J. Szabados (Eds.), Trends and Applications in Constructive Approximation, International Series of Numerical Mathematics, vol. 151, Birkhäuser, Basel, 2005, pp. 103-123.
26. Y. Jin T. Okabe B. Sendhoff Neural network regularization and ensembling using multi-objective evolutionary algorithms in: Proceedings of the Congress on Evolutionary Computation (CEC'04) 2004 IEEE Press New York 1-8
27. E. Karnin A simple procedure for pruning back-propagation trained networks IEEE Trans. Neural Networks 1 2 1990 239-242
28. J. Kaszubiak M. Tornow R. Kuhn B. Michaelis C. Knoeppel Real-time vehicle and lane detection with embedded hardware in: Proceedings of the IEEE Symposium on Intelligent Vehicles 2005 619-624
29. J. Knowles, L. Thiele, E. Zitzler, A tutorial on the performance assessment of stochastic multiobjective optimizers, Computer Engineering and Networks Laboratory (TIK), vol. 214, Swiss Federal Institute of Technology (ETH), Zurich, July 2005.
30. M. Lades J.C. Vorbrüggen J. Buhmann J. Lange C. von der Malsburg R.P. Würtz W. Konen Distortion invariant object recognition in the dynamic link architecture IEEE Trans.Comput. 42 1993 301-311
31. S. Nolfi Evolution and learning in neural networks M.A. Arbib The Handbook of Brain Theory and Neural Networks 2nd ed. 2002 MIT Press Cambridge, MA 415-418
32. T. Okabe Y. Jin B. Sendhoff A critical survey of performance indices for multi-objective optimisation in: Proceedings of the 2003 Congress on Evolutionary Computation (CEC'03) 2003 IEEE Press New York 1053-1060
33. R.D. Reed R.J. Marks II Neural Smithing 1999 MIT Press Cambridge, MA
34. M. Riedmiller Advanced supervised learning in multi-layer perceptrons - From backpropagation to adaptive learning algorithms Comput. Standards and Interfaces 16 5 1994 265-278
35. H.A. Rowley S. Baluja T. Kanade Neural network-based face detection IEEE Trans. Pattern Anal. Mach. Intell. 20 1 1998 23-38
36. A. Shashua Y. Gdalyahu G. Hayun Pedestrian detection for driving assistance systems: Single-frame classification and system level performance in: Proceedings of the IEEE Symposium on Intelligent Vehicles 2004 1-6
37. J.E. Smith T.C. Fogarty Operator and parameter adaptation in genetic algorithms Soft Comput. 1 2 1997 81-87
38. A. Stahlberger M. Riedmiller Fast network pruning and feature extraction by using the unit-OBS algorithm M.C. Mozer M.I. Jordan T. Petsche Advances in Neural Information Processing Systems vol. 9 1997 The MIT Press Cambridge, MA 655-661
39. M. Szarvas A. Yoshizawa M. Yamamoto J. Ogata Pedestrian detection using convolutional neural networks in: Proceedings of the IEEE Symposium on Intelligent Vehicles 2005 224-229
40. Viisage Technology AG, 〈http://www.viisage.com〉.
41. A.S. Weigend D.E. Rumelhart B. Huberman Back-propagation, weight elimination and time series prediction D. Touretzky J. Elman T. Sejnowski G. Hinton Proceedings of the 1990 Connectionist Models Summer School 1991 Morgan Kaufmann Sant Matteo 105-116
42. L.D. Whitley The GENITOR algorithm and selection pressure: Why rank-based allocation of reproductive trials is best J.D. Schaffer Proceedings of the Third International Conference on Genetic Algorithms, ICGA'89 1989 Morgan Kaufmann Los Altos, CA 116-121
43. S. Wiegand C. Igel U. Handmann Evolutionary multi-objective optimisation of neural networks for face detection Internat. J. Comput. Intell. Appl. 4 3 2004 237-253
44. S. Wiegand C. Igel U. Handmann Evolutionary optimization of neural networks for face detection in: M. Verleysen 12th European Symposium on Artificial Neural Networks (ESANN 2004) 2004 d-side publications Evere, Belgium 139-144
45. C. Wöhler J.K. Anlauf Real-time object recognition on image sequences with the adaptable time delay neural network algorithm-applications for autonomous vehicles Image and Vision Comput. 19 9-10 2001 593-618
46. J.M. Wolfe Visual search H.D. Pashler Attention 1998 University College London Press London, UK
47. M.-H. Yang D.J. Kriegman N. Ahuja Detecting faces in images: A survey IEEE Trans. Pattern Anal. Mach. Intell. 24 1 2002 34-58
48. X. Yao Evolving artificial neural networks Proc. IEEE 87 9 1999 1423-1447
49. G.P. Zhang Neural networks for classification: A survey IEEE Trans. Syst. Man Cybernet. C 30 4 2000 451-462
50. W. Zhao R. Chellappa P. Phillips A. Rosenfeld Face recognition: A literature survey ACM Comput. Surveys (CSUR) 35 4 2003 399-458
51. E. Zitzler L. Thiele M. Laumanns C.M. Fonseca V.G. da Fonseca Performance assessment of multiobjective optimizers: An analysis and review IEEE Trans. Evol. Comput. 7 2 2003 117-132