Is quantity better than quality?: a study case on a simple classifier applied to digit character recognition (パターン認識・メディア理解)
スポンサーリンク
概要
- 論文の詳細を見る
This paper deals with a learning method for digit character recognition. We propose to expand character image databases, by automatically generating deformations, noises and new fonts, and then to use a simple classifier based on k nearest neighbor technique. The results of first experiments show that the classifier is more robust on the resulting larger database. Moreover, performance on the MNIST digit character database is very promising.
- 社団法人電子情報通信学会の論文
- 2010-08-29
著者
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Omachi Shinichiro
Graduate School Of Engineering Tohoku University
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KISE Koichi
Department of Computer Science and Intelligent Systems, Osaka Prefecture University
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IWAMURA Masakazu
Department of Computer Science and Intelligent Systems, Osaka Prefecture University
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Kise Koichi
Department Of Computer Science And Intelligent Systems Osaka Prefecture University
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Kise Koichi
Graduate School Of Engineering Osaka Prefecture University
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Iwamura Masakazu
Graduate School Of Engineering Osaka Prefecture University
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Iwamura Masakazu
Department Of Computer Science And Intelligent Systems Osaka Prefecture University
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Barrat Sabine
Graduate School Of Engineering Osaka Prefecture University:japan Society For The Promotion Of Scienc
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Uchida Seiichi
Faculty Of Information Science And Electrical Engineering Kyushu University
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ALARY Geoffrey
Graduate School of Engineering, Osaka Prefecture University
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Alary Geoffrey
Graduate School Of Engineering Osaka Prefecture University:eisti Computer Science And Mathematics En
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