Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

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. Use...

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Bibliographic Details
Published in:Journal of physics. Conference series 2016-08, Vol.738 (1), p.12123
Main Authors: Popko, E.A., Weinstein, I.A.
Format: Article
Language:English
Subjects:
Algorithms
Artificial neural networks
Codes
Computer architecture
Digits
Fuzzy logic
Handwriting recognition
Modules
Neural networks
Optical character recognition
Pattern recognition
Physics
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Summary: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.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/738/1/012123