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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.
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Fukushima et al. (Thu,) studied this question.
www.synapsesocial.com/papers/6a01be32f58f6e6cfdd8bd4b — DOI: https://doi.org/10.1109/tsmc.1983.6313076
Kunihiko Fukushima
Sei Miyake
Takayuki Ito
IEEE Transactions on Systems Man and Cybernetics
Japan Broadcasting Corporation (Japan)
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