Handwritten Postal Code Recognition by Neural Network : A Comparative Study (Special Issue on Character Recognition and Document Understanding)
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概要
- 論文の詳細を見る
This paper compares some popular character recognition techniques which have been proposed until today. 17 feature extraction methods and 4 neural network based recognition processes were used in handwritten numerals (postal codes)recognition. It was found that Weighted Direction Index Histogram, Peripheral Direction Contributivity Function and Expansion Cell feature extractions gave good results. As for the neural network recognition process, Comb NET-II and multi layer neural network showed good performances.
- 社団法人電子情報通信学会の論文
- 1996-05-25
著者
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TAKAHASHI Hidekazu
Department of Dental Technology I, Faculty of Dentistry, Tokyo Medical and Dental University
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Takahashi H
Univ. Tokyo Tokyo Jpn
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IWATA Akira
Department of Computer Science & Engineering, Nagoya Institute of Technology
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Tsutsumida Toshio
Technology Department Research Center Institute Of Posts And Telecommunications:ministry Of Posts An
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Tsutsumida Toshio
Technology Department Research Center Institute For Posts And Telecommunications Policy Ministry Of
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Iwata Akira
Department Of Electrical And Computer Engineering Nagoya Institute Of Technology
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ARIF Ahmad
Department of Electrical and Computer Engineering, Nagoya Institute of Technology
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Arif Ahmad
Department Of Electrical And Computer Engineering Nagoya Institute Of Technology
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Takahashi Hidekazu
Department Of Dental Technology 1 Faculty Dentistry Tokyo Medical And Dental University
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Takahashi Hidekazu
Department Of Advanced Biomaterials Division Of Oral Health Sciences Graduate School Tokyo Medical A
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