Presentation | 1995/7/20 High Accuracy Recognition of ETL9B using Exclusive Learning Neural Network-II (ELNET-II) Kazuki Saruta, Ning Sun, Masato Abe, Yoshiaki Nemoto, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We have already proposed Exclusive Learning neural NETwork (ELNET) as neural network which can be easily utilized to construct a recognition system for Chinese character. In this paper, we propose ELNET-II, which is improved version of ELNET and use more effective learning algorithm. In ELNET, some problem such effect of learning remained. In ELNET-II, the number of learning data and module size variable according to candidate appearance frequency in rough classification. In recognition experiment for ETL9B (3036 categories), we have gotten 95.84% as maximum recognition rate. In comparison with ELNET, the rate improved about 1.3%. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | handwritten character recognition / neural networks / ETL9B / ELNET-II |
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Committee | PRU |
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Conference Date | 1995/7/20(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Understanding (PRU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | High Accuracy Recognition of ETL9B using Exclusive Learning Neural Network-II (ELNET-II) |
Sub Title (in English) | |
Keyword(1) | handwritten character recognition |
Keyword(2) | neural networks |
Keyword(3) | ETL9B |
Keyword(4) | ELNET-II |
1st Author's Name | Kazuki Saruta |
1st Author's Affiliation | Graduate School of Information Sciences, Tohoku Univ.() |
2nd Author's Name | Ning Sun |
2nd Author's Affiliation | Graduate School of Information Sciences, Tohoku Univ. |
3rd Author's Name | Masato Abe |
3rd Author's Affiliation | Computer Center, Tohoku Univ. |
4th Author's Name | Yoshiaki Nemoto |
4th Author's Affiliation | Graduate School of Information Sciences, Tohoku Univ. |
Date | 1995/7/20 |
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Volume (vol) | vol.95 |
Number (no) | 164 |
Page | pp.pp.- |
#Pages | 6 |
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