| Title: | OS11-6 The recognition and implementation of handwritten character based on deep learning |
|---|---|
| Publication: | ICAROB2019 |
| Volume: | 24 |
| Pages: | 276-279 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2019.OS11-6 |
| Author(s): | Zhongyong Ye, Fengzhi Dai, Xia Jin, Yasheng Yuan, Lingran An, Yujie Yan, Yiqiao Qin, Hao Li |
| Publication Date: | January 10, 2019 |
| Keywords: | Deep learning, Machine learning, Pattern recognition, Handwriting character recognition, Convolution neural network |
| Abstract: | This paper mainly focuses on the recognition of handwritten characters, especially handwritten Chinese characters. Using deep learning technology constructs a deep convolution neural network to identify the character set of handwritten Chinese characters, compares the performance differences of the same depth network, and finally gets the network structure which can be used for recognition, and realizes the recognition system of handwritten characters based on the network. By comparing with other hand writing characters, the engineering application value of the network structure used in this paper is proved, and finally the handwriting character recognition system based on this model also embodies the feasibility of the network structure in this paper. |
| PDF File: | https://alife-robotics.co.jp/members2019/icarob/data/html/data/OS_pdf/OS11/OS11-6.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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