Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

5th International Conference on Mathematical Modeling in Physical Sciences

物理学;数学

Popko, E.A.^1 ; Weinstein, I.A.^1

NANOTECH Centre, Ural Federal University, Mira Street, 19, Yekaterinburg, Russia^1

关键词: Convolutional neural network;    Handwritten digit;    Handwritten digits recognition;    Recognition rates;    Structural approach;    Used systems;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/738/1/012123/pdf
DOI  :  10.1088/1742-6596/738/1/012123

来源: IOP

【 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.