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Neocognitron Applied to Handwritten Digit Recognition : Evaluation with ETL Character Database
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- NAGAHARA Ken-ichi
- Department of Biophysical Engineering, Faculty of Engineering Science, Osaka University
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- SHOUNO Hayaru
- Department of Biophysical Engineering, Faculty of Engineering Science, Osaka University
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- FUKUSHIMA Kunihiko
- Department of Biophysical Engineering, Faculty of Engineering Science, Osaka University
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- OKADA Masato
- Department of Biophysical Engineering, Faculty of Engineering Science, Osaka University
Bibliographic Information
- Other Title
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- ネオコグニトロンの実用化 : ETL文字データベースによる評価
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Description
The neocognitron is a neural network model which has the ability to recognize patterns. In our previous work, we obtained a recognition rate of 92.7% for handwritten digits in the ETL-1 database by using a high threshold for feature-extracting cells in the learning phase and a lower threshold in the recognition phase. In this paper, we changed learning method of the highest stage, and increased the number of the training patterns so that we obtained a recognition rate of 97.4%.
Journal
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- IEICE technical report. Neurocomputing
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IEICE technical report. Neurocomputing 95 (598), 255-261, 1996-03-18
The Institute of Electronics, Information and Communication Engineers
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Keywords
Details 詳細情報について
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- CRID
- 1570291227539117184
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- NII Article ID
- 110003233139
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- NII Book ID
- AN10091178
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- Text Lang
- ja
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- Data Source
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- CiNii Articles