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Rotation-Invariant Pattern Recognition: A Procedure Slightly Inspired on Olfactory System and Based on Kohonen Network
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Pattern Recognition
Rotation-Invariant Pattern Recognition: A Procedure Slightly Inspired on Olfactory System and Based on Kohonen Network
M. B. Palermo1 and L. H. A. Monteiro1, 2 
| (1) |
Universidade Presbiteriana Mackenzie, Pós-graduação em Engenharia Elétrica, Escola de Engenharia, Rua da Consolação, n.896,
01302-907, São Paulo, SP, Brazil |
| (2) |
Universidade de São Paulo, Departamento de Engenharia de Telecomunicações e Controle, Escola Politécnica, Av Prof. Luciano
Gualberto, travessa 3, n.380, 05508-900, São Paulo, SP, Brazil |
Abstract
A computational scheme for rotation-invariant pattern recognition based on Kohonen neural network is developed. This scheme
is slightly inspired on the vertebrate olfactory system, and its goal is to recognize spatiotemporal patterns produced in
a two-dimensional cellular automaton that would represent the olfactory bulb activity when submitted to odor stimuli. The
recognition occurs through a multi-layer Kohonen network that would represent the olfactory cortex. The recognition is invariant
to rotations of the patterns, even when a noise lower than 1% is added.
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