Hierarchies of autoassociators

Proceedings - International Conference on Pattern Recognition

Volumn 4, Issue , 1996, Pages 200-204

  Weingessel, A ^a   Bischof, H ^a   Hornik, K ^a  

^a VIENNA UNIVERSITY OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE EXTRACTION;

AUTOASSOCIATORS; HIERARCHICAL NEURAL NETWORKS; PRINCIPAL COMPONENTS; WEIGHT CONSTRAINTS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 0001482381     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.1996.547415     Document Type: Conference Paper

References (10)

1. P. F. Baldi and K. Homik. Learning in linear neural networks: A survey. IEEE Transactions on Neural Networks, 6(4):837-858, July 1995.
2. H. Bischof. Pyramidal Neural Networks. Lawrence Erlbaum Associates, 1995.
3. H. Bischof and K. Homik. PCA-Pyramids for image compression. In G. Tesauro, D. Touretzky, and T. Leen, editors, Advances in Neural Information Processing Systems (NIPS?94), volume 7. pages 941-948. Press, 1995.
4. K. Fukushima, S. Miyake, and T. Ito. Neocognitron: A neural network model for a mechanism of visual pattem recognition. IEEE Transactions on Systems, Man, and Cybernetics, 13(3):826-834, Sept/Oct. 1983.
5. K. Homik and C. M. Kuan. Convergence analysis of local feature extraction algorithms. Neural Networks, 5(2):229-240, 1992.
6. J.-M. Jolion and A. Rosenfeld. A Pyramid Framework for Early Vision. Boston: Kluwer, 1994.
7. Y. Le Cun, O. Matan, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, L. D. Jackel, and H. S. Baird. Handwritten ZIP code recognition with multilayer networks. In Proceedings of the 10 International Conference on Pattern Recognition, pages 35-40. Washington: BEE Computer Society Press, 1990.
8. A. Rosenfeld, editor. Multiresolution Image Processing and Analysis. Berlin: Springer-Verlag, 1984.
9. J. K. Tsotsos. Analyzing vision at the complexity level. Behavioral and Brain Sciences, 13(3):423-469, 1990.
10. L. Uhr. Cycling logarithmically converging networks that flow information to behave (perceive) and learn. In W. H., editor, Neural Networks for Perception, volume 2, pages 147-172. Academic Press, Inc., 1992.