OS16-3 Research on a Method of Character Recognition for Self-learning Errors

Title:	OS16-3 Research on a Method of Character Recognition for Self-learning Errors
Publication:	ICAROB2017
Volume:	22
Pages:	190-193
ISSN:	2188-7829
DOI:	10.5954/ICAROB.2017.OS16-3
Author(s):	Huailin Zhao, Yawei Hou, Shifang Xu, Congdao Han, Masanori Sugisaka
Publication Date:	January 19, 2017
Keywords:	probabilistic neural network, handwritten numeral recognition, self-learning, matlab
Abstract:	Due to the different writing habits, the handwritten numeral is difficult to identify. No matter what kind of network, the computer can not judge the output of the network. This reduces the recognition rate of the network. In order to improve the recognition rate, this paper proposes a method of character recognition for self-learning errors. Finally, on the matlab simulation platform, it is proved that the method proposed in this paper can improve the recognition accuracy.
PDF File:	https://alife-robotics.co.jp/members2017/icarob/data/html/data/OS_pdf/OS16/OS16-3.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/