Presentation 1997/6/19
Neocognitron applied to Handwritten Digit Recognition : Evaluation with Large Character Database
Hayaru SHOUNO, Ken-ichi Nagahara, Kunihiko FUKUSHIMA, Masato Okada,
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Abstract(in English) The neocognitron is a hierachical neural network model of the visual processing system like mamals. It has ability to recognize pattern. In this paper, we improve the neocognitron for real world digit pattern recognition. The neocognitron classify a input digit pattern by the shape of the pattern. We introduce a new layer after the neocognitron system for pattern classifying the ten digit categories. The category classifying layer classify the output of the neocognitron to a category from '0' to '9'. We evaluate the performance of the neocognitron with category classifing network using ETL-1 database.
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Keyword(in English) Pattern Recognition / Neocognitron / Pattern Classifier / ETL-1 database
Paper # NC97-19
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Committee NC
Conference Date 1997/6/19(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Neocognitron applied to Handwritten Digit Recognition : Evaluation with Large Character Database
Sub Title (in English)
Keyword(1) Pattern Recognition
Keyword(2) Neocognitron
Keyword(3) Pattern Classifier
Keyword(4) ETL-1 database
1st Author's Name Hayaru SHOUNO
1st Author's Affiliation Osaka University, Graduate School of Engineering Science()
2nd Author's Name Ken-ichi Nagahara
2nd Author's Affiliation Osaka University, Graduate School of Engineering Science
3rd Author's Name Kunihiko FUKUSHIMA
3rd Author's Affiliation Osaka University, Graduate School of Engineering Science
4th Author's Name Masato Okada
4th Author's Affiliation Exploratory Research for Advanced Technology(ERATO)
Date 1997/6/19
Paper # NC97-19
Volume (vol) vol.97
Number (no) 116
Page pp.pp.-
#Pages 7
Date of Issue