Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/20.500.12258/528
Full metadata record
DC FieldValueLanguage
dc.contributor.authorChervyakov, N. I.-
dc.contributor.authorЧервяков, Н. И.-
dc.contributor.authorLyakhov, P. A.-
dc.contributor.authorЛяхов, П. А.-
dc.contributor.authorValueva, M. V.-
dc.contributor.authorВалуева, М. В.-
dc.date.accessioned2018-06-08T08:27:16Z-
dc.date.available2018-06-08T08:27:16Z-
dc.date.issued2017-
dc.identifier.citationChervyakov, 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.ru
dc.identifier.urihttps://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=-
dc.identifier.urihttps://dspace.ncfu.ru:443/handle/20.500.12258/528-
dc.description.abstractThis 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 realizationru
dc.language.isoenru
dc.publisherInstitute of Electrical and Electronics Engineers Inc.ru
dc.relation.ispartofseriesProceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017-
dc.subjectConvolutional Neural Network (CNN)ru
dc.subjectImage processingru
dc.subjectPattern recognitionru
dc.subjectResidue number system (RNS)ru
dc.titleIncreasing of convolutional neural network performance using residue number systemru
dc.typeСтатьяru
vkr.amountPages 135-140ru
vkr.instИнститут математики и естественных наук-
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

Files in This Item:
File Description SizeFormat 
scopusresults (75).pdf
  Restricted Access
62.44 kBAdobe PDFView/Open
WoS 43 .pdf
  Restricted Access
80.58 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.