Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition / Popko E. A.,Weinstein I. A. // . - 2016. - V. 738, l. .

ISSN/EISSN:

1742-6588 / нет данных

Type:

Proceedings Paper

Abstract:

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.

Author keywords:

THERMOLUMINESCENCE

DOI:

10.1088/1742-6596/738/1/012123

Web of Science ID:

ISI:000403403900123

Соавторы в МНС:

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Другие поля

Поле	Значение
Editor	Vagenas, EC and Vlachos, DS
Booktitle	5TH INTERNATIONAL CONFERENCE ON MATHEMATICAL MODELING IN PHYSICAL SCIENCES (IC-MSQUARE 2016)
Series	Journal of Physics Conference Series
Note	5th International Conference on Mathematical Modeling in Physical Sciences (IC-MSquare), Athens, GREECE, MAY 23-26, 2016
Publisher	IOP PUBLISHING LTD
Address	DIRAC HOUSE, TEMPLE BACK, BRISTOL BS1 6BE, ENGLAND
Language	English
Article-Number	UNSP 012123
Keywords-Plus	THERMOLUMINESCENCE
Research-Areas	Mathematics; Physics
Web-of-Science-Categories	Mathematics, Applied; Physics, Mathematical
Author-Email	e.a.popko@urfu.ru
Funding-Acknowledgement	Act 211 Government of the Russian Federation {[}02.A03.21.0006]
Funding-Text	This work was supported by contract No 02.A03.21.0006, Act 211 Government of the Russian Federation.
Number-of-Cited-References	14
Usage-Count-Since-2013	1
Doc-Delivery-Number	BH8KX