Increasing of convolutional neural network performance using residue number system

This paper considers the method of pattern recognition based on a convolutional neural network using Sobel filters. Parameters of the convolutional neural network blocks were chosen experimentally by software modeling in MATLAB. We presents the architecture of the convolutional neural network constr...

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Asıl Yazarlar:	Chervyakov, N. I., Червяков, Н. И., Lyakhov, P. A., Ляхов, П. А., Valueva, M. V., Валуева, М. В.
Materyal Türü:	Статья
Dil:	English
Baskı/Yayın Bilgisi:	Institute of Electrical and Electronics Engineers Inc. 2018
Konular:	Convolutional Neural Network (CNN) Image processing Pattern recognition Residue number system (RNS)
Online Erişim:	https://www.scopus.com/record/display.uri?eid=2-s2.0-85040520452&origin=resultslist&sort=plf-f&src=s&nlo=1&nlr=20&nls=afprfnm-t&affilName=nort+caucas+fed+univ&sid=6e44c4739f67eaef119fa92298a82e4b&sot=afnl&sdt=sisr&sl=53&s=%28AF-ID%28%22North+Caucasus+Federal+University%22+60070541%29%29&ref=%28Increasing+of+convolutional+neural+network+performance+using+residue+number%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru:443/handle/20.500.12258/528
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spelling	ir-20.500.12258-5282020-07-06T13:05:06Z Increasing of convolutional neural network performance using residue number system Chervyakov, N. I. Червяков, Н. И. Lyakhov, P. A. Ляхов, П. А. Valueva, M. V. Валуева, М. В. Convolutional Neural Network (CNN) Image processing Pattern recognition Residue number system (RNS) This paper considers the method of pattern recognition based on a convolutional neural network using Sobel filters. Parameters of the convolutional neural network blocks were chosen experimentally by software modeling in MATLAB. We presents the architecture of the convolutional neural network constructed with residue number system for delay minimization. Using of special type of modules allows to accelerate the work of the device by 37,4% as compared to using a binary number system and by 18,5% as compared to using a known residue number system realization 2018-06-08T08:27:16Z 2018-06-08T08:27:16Z 2017 Статья Chervyakov, N.I., Lyakhov, P.A., Valueva, M.V. Increasing of convolutional neural network performance using residue number system // Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. - 2017. - статья № 8109855. - pp. 135-140. https://www.scopus.com/record/display.uri?eid=2-s2.0-85040520452&origin=resultslist&sort=plf-f&src=s&nlo=1&nlr=20&nls=afprfnm-t&affilName=nort+caucas+fed+univ&sid=6e44c4739f67eaef119fa92298a82e4b&sot=afnl&sdt=sisr&sl=53&s=%28AF-ID%28%22North+Caucasus+Federal+University%22+60070541%29%29&ref=%28Increasing+of+convolutional+neural+network+performance+using+residue+number%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru:443/handle/20.500.12258/528 en Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017 application/pdf application/pdf Institute of Electrical and Electronics Engineers Inc.
institution	СКФУ
collection	Репозиторий
language	English
topic	Convolutional Neural Network (CNN) Image processing Pattern recognition Residue number system (RNS)
spellingShingle	Convolutional Neural Network (CNN) Image processing Pattern recognition Residue number system (RNS) Chervyakov, N. I. Червяков, Н. И. Lyakhov, P. A. Ляхов, П. А. Valueva, M. V. Валуева, М. В. Increasing of convolutional neural network performance using residue number system
description	This paper considers the method of pattern recognition based on a convolutional neural network using Sobel filters. Parameters of the convolutional neural network blocks were chosen experimentally by software modeling in MATLAB. We presents the architecture of the convolutional neural network constructed with residue number system for delay minimization. Using of special type of modules allows to accelerate the work of the device by 37,4% as compared to using a binary number system and by 18,5% as compared to using a known residue number system realization
format	Статья
author	Chervyakov, N. I. Червяков, Н. И. Lyakhov, P. A. Ляхов, П. А. Valueva, M. V. Валуева, М. В.
author_facet	Chervyakov, N. I. Червяков, Н. И. Lyakhov, P. A. Ляхов, П. А. Valueva, M. V. Валуева, М. В.
author_sort	Chervyakov, N. I.
title	Increasing of convolutional neural network performance using residue number system
title_short	Increasing of convolutional neural network performance using residue number system
title_full	Increasing of convolutional neural network performance using residue number system
title_fullStr	Increasing of convolutional neural network performance using residue number system
title_full_unstemmed	Increasing of convolutional neural network performance using residue number system
title_sort	increasing of convolutional neural network performance using residue number system
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2018
url	https://www.scopus.com/record/display.uri?eid=2-s2.0-85040520452&origin=resultslist&sort=plf-f&src=s&nlo=1&nlr=20&nls=afprfnm-t&affilName=nort+caucas+fed+univ&sid=6e44c4739f67eaef119fa92298a82e4b&sot=afnl&sdt=sisr&sl=53&s=%28AF-ID%28%22North+Caucasus+Federal+University%22+60070541%29%29&ref=%28Increasing+of+convolutional+neural+network+performance+using+residue+number%29&relpos=0&citeCnt=0&searchTerm= https://dspace.ncfu.ru:443/handle/20.500.12258/528
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_version_	1760599808598343680

Increasing of convolutional neural network performance using residue number system

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