DocumentCode :
1298869
Title :
Neocognitron: A neural network model for a mechanism of visual pattern recognition
Author :
Fukushima, Kazuki ; Miyake, S. ; Ito, Takao
Author_Institution :
NHK Broadcasting Sci. Res. Labs., Tokyo, Japan
Issue :
5
fYear :
1983
Firstpage :
826
Lastpage :
834
Abstract :
A recognition with a large-scale network is simulated on a PDP-11/34 minicomputer and is shown to have a great capability for visual pattern recognition. The model consists of nine layers of cells. The authors demonstrate that the model can be trained to recognize handwritten Arabic numerals even with considerable deformations in shape. A learning-with-a-teacher process is used for the reinforcement of the modifiable synapses in the new large-scale model, instead of the learning-without-a-teacher process applied to a previous model. The authors focus on the mechanism for pattern recognition rather than that for self-organization.
Keywords :
digital simulation; neural nets; pattern recognition; visual perception; PDP-11/34 minicomputer; digital simulation; handwritten Arabic numerals; large-scale network; learning-with-a-teacher process; modifiable synapses; neural network model; recognition; reinforcement; visual pattern recognition; visual perception; Biological neural networks; Brain modeling; Computational modeling; Pattern recognition; Shape; Training; Visualization;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/TSMC.1983.6313076
Filename :
6313076
Link To Document :
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