Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

被引：14
|
作者：
Popko, E. A. [1 ]
Weinstein, I. A. [1 ]
机构：
[1] Ural Fed Univ, NANOTECH Ctr, Mira St 19, Ekaterinburg, Russia
来源：
5TH INTERNATIONAL CONFERENCE ON MATHEMATICAL MODELING IN PHYSICAL SCIENCES (IC-MSQUARE 2016) | 2016年 / 738卷
关键词：
THERMOLUMINESCENCE;
D O I：
10.1088/1742-6596/738/1/012123
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Optical character recognition is one of the important issues in the field of pattern recognition. This paper presents a method for recognizing handwritten digits based on the modeling of convolutional neural network. The integrated fuzzy logic module based on a structural approach was developed. Used system architecture adjusted the output of the neural network to improve quality of symbol identification. It was shown that proposed algorithm was flexible and high recognition rate of 99.23% was achieved.
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页数：6
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