High Accuracy Recognition of ETL9B Using Exclusive Learning Neural Network-II : ELNET-II (Special Issue on Character Recognition and Document Understanding)
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概要
- 論文の詳細を見る
In earlier works we proposed the Exclusive Learning neural NETwork (ELNET), which can be utilized to construct large scale recognition system for Chinese characters. However, this did not resolve the problem of how to use training samples effectively to generate more suitable recognition boundaries. In this paper, we propose ELNET-II wherein an attempt has been made to deal with this problem. In comparison with ELNET, selection method of training samples is improved. And the number of module size are variable according to the number of training samples for each module. In recognition experiment for ETL9B (3036 categories) using ELNET-II, we obtained a recognition rate of 95.84% as maximum recognition rate. This is the first time that such a high recognition rate has been obtained by neural networks.
- 社団法人電子情報通信学会の論文
- 1996-05-25
著者
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KATO Nei
Graduate School of Information Sciences, Tohoku University
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NEMOTO Yoshiaki
Graduate School of Information Sciences, Tohoku University
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Kato Naoki
The Central Research Laboratory Hitachi Ltd.
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Nemoto Y
Graduate School Of Information Sciences (gsis) Tohoku University
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Nemoto Y
Graduate School Of Information Sciences Tohoku University
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Abe Masato
Faculty Of Engineering Iwate University
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Kato N
Graduate School Of Information Sciences Tohoku University
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Kato Nei
Graduate School Of Information Sciences (gsis) Tohoku University
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SARUTA Kazuki
Faculty of Literature and Social Sciences, Yamagata University
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Nemoto Yoshiaki
Graduate School Of Information Science Tohoku University
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Saruta Kazuki
The Author Is With The Faculty Of Systems Science And Technology Akita Prefectural Univ.
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