Emergence of phase- and shift-invariant features by decomposition of natural images into independent feature subspaces

Neural Computation

Volumn 12, Issue 7, 2000, Pages 1705-1720

  Hyvärinen, Aapo ^a   Hoyer, Patrik ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BIOLOGICAL MODEL; LEARNING; NERVE CELL; PATTERN RECOGNITION; PHYSIOLOGY; SIGNAL PROCESSING;

LEARNING; MODELS, NEUROLOGICAL; NEURONS; PATTERN RECOGNITION, VISUAL; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 0034222304     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976600300015312     Document Type: Article

References (24)

1. Barlow, H. (1989). Unsupervised learning. Neural Computation, 1, 295-311.
2. Barlow, H. (1994). What is the computational goal of the neocortex? In C. Koch & J. Davis (Eds.), Large-scale neuronal theories of the brain. Cambridge, MA: MIT Press.
3. Bell, A., & Sejnowski,T. (1997). The "independent components" of natural scenes are edge filters. Vision Research, 37, 3327-3338.
4. Cardoso, J. F. (1998). Multidimensional independent component analysis. In Proc. ICASSP'98 (Seattle, WA).
5. Cardoso, J.-E, & Laheld, B. H. (1996). Equivariant adaptive source separation. IEEE Trans, on Signal Processing, 44(12), 3017-3030.
6. Comon, P. (1994). Independent component analysis - a new concept? Signal Processing, 36, 287-314.
7. Field, D. (1994). What is the goal of sensory coding? Neural Computation, 6, 559-601.
8. Földíak, P. (1991). Learning invariance from transformation sequences. Neural Computation, 3, 194-200.
9. Heeger, D. (1992). Normalization of cell responses in cat striate cortex. Visual Neuroscience, 9, 181-198.
10. Hubel, D., & Wiesel, T. (1962). Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. Journal of Physiology, 73, 218-226.
11. Hyvärinen, A., & Oja, E. (1997). A fast fixed-point algorithm for independent component analysis. Neural Computation, 9(7), 1483-1492.
12. Hyvärinen, A., & Oja, E. (1998). Independent component analysis by general nonlinear Hebbian-like learning rules. Signal Processing, 64(3), 301-313.
13. Karhunen, J., Oja, E., Wang, E., Vigario, R., & Joutsensalo, J. (1997). A class of neural networks for independent component analysis. IEEE Trans. on Neural Networks, 8(3), 486-504.
14. Kohonen, T. (1995). Self-organizing maps. Berlin: Springer-Verlag.
15. Kohonen, T. (1996). Emergence of invariant-feature detectors in the adaptive-subspace self-organizing map. Biological Cybernetics, 75, 281-291.
16. Mel, B. W., Ruderman, D. E., & Archie, K. A. (1998). Translation-invariant orientation tuning in visual "complex" cells could derive from intradendritic computations. Journal of Neuroscience, 18, 43254-334.
17. Olshausen, B. A., & Field, D. J. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature, 381, 607-609.
18. Olshausen, B. A., & Field, D. J. (1997). Sparse coding with an overcomplete basis set: A strategy employed by V1? Vision Research, 37, 3311-3325.
19. Pham, D.-T., Garrat, P., & Jutten, C. (1992). Separation of a mixture of independent sources through a maximum likelihood approach. In Proc. EUSIPCO (pp. 771-774).
20. Pollen, D., & Ronner, S. (1983). Visual cortical neurons as localized spatial frequency filters. IEEE Trans. on Systems, Man, and Cybernetics, 13, 907-916.
21. van Hateren, J. H., & Ruderman, D. L. (1998). Independent component analysis of natural image sequences yields spatiotemporal filters similar to simple cells in primary visual cortex. Proc. Royal Society ser. B, 265, 2315-2320.
22. van Hateren, J. H., & van der Schaaf, A. (1998). Independent component filters of natural images compared with simple cells in primary visual cortex. Proc. Royal Society ser. B, 265, 359-366.
23. von der Heydt, R. (1995). Form analysis in visual cortex. In M. S Gazzaniga (Ed.), The cognitive neurosciences (pp. 365-382). Cambridge, MA: MIT Press.
24. von der Malsburg, C., Shams, L., & Eysel, U. (1998). Recognition of images from complex cell responses. Abstract presented at at Proc. of Society for Neuroscience Meeting.