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Recognition of deaf gestures based on a bio-inspired neural network. / Grif, M. G.; Kugaevskikh, A. V.

In: Journal of Physics: Conference Series, Vol. 1661, No. 1, 012038, 10.11.2020.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Grif, MG & Kugaevskikh, AV 2020, 'Recognition of deaf gestures based on a bio-inspired neural network', Journal of Physics: Conference Series, vol. 1661, no. 1, 012038. https://doi.org/10.1088/1742-6596/1661/1/012038

APA

Grif, M. G., & Kugaevskikh, A. V. (2020). Recognition of deaf gestures based on a bio-inspired neural network. Journal of Physics: Conference Series, 1661(1), [012038]. https://doi.org/10.1088/1742-6596/1661/1/012038

Vancouver

Grif MG, Kugaevskikh AV. Recognition of deaf gestures based on a bio-inspired neural network. Journal of Physics: Conference Series. 2020 Nov 10;1661(1):012038. doi: 10.1088/1742-6596/1661/1/012038

Author

Grif, M. G. ; Kugaevskikh, A. V. / Recognition of deaf gestures based on a bio-inspired neural network. In: Journal of Physics: Conference Series. 2020 ; Vol. 1661, No. 1.

BibTeX

@article{edfbae8d07344a628a6b6950af559987,
title = "Recognition of deaf gestures based on a bio-inspired neural network",
abstract = "In this paper discusses the current situation in Russia and the world in the field of development of sign languages translation system. The main problems are formulated, and ways to solve them are given. One of the most important unresolved tasks is the task of recognizing the gestures of the deaf. To effectively solve it, an approach based on the development of bio-inspired neural networks is proposed. The architecture of a bio-inspired neural network, including four types of neurons, is described. New simpler MT neuron model proposed. ",
author = "Grif, {M. G.} and Kugaevskikh, {A. V.}",
note = "Funding Information: This paper was financially supported by the Russian Foundation for Basic Research (Grant No. 19-57-45006). Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2020 International Conference on Information Technology in Business and Industry, ITBI 2020 ; Conference date: 06-04-2020 Through 08-04-2020",
year = "2020",
month = nov,
day = "10",
doi = "10.1088/1742-6596/1661/1/012038",
language = "English",
volume = "1661",
journal = "Journal of Physics: Conference Series",
issn = "1742-6588",
publisher = "IOP Publishing Ltd.",
number = "1",

}

RIS

TY - JOUR

T1 - Recognition of deaf gestures based on a bio-inspired neural network

AU - Grif, M. G.

AU - Kugaevskikh, A. V.

N1 - Funding Information: This paper was financially supported by the Russian Foundation for Basic Research (Grant No. 19-57-45006). Publisher Copyright: © Published under licence by IOP Publishing Ltd. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/11/10

Y1 - 2020/11/10

N2 - In this paper discusses the current situation in Russia and the world in the field of development of sign languages translation system. The main problems are formulated, and ways to solve them are given. One of the most important unresolved tasks is the task of recognizing the gestures of the deaf. To effectively solve it, an approach based on the development of bio-inspired neural networks is proposed. The architecture of a bio-inspired neural network, including four types of neurons, is described. New simpler MT neuron model proposed.

AB - In this paper discusses the current situation in Russia and the world in the field of development of sign languages translation system. The main problems are formulated, and ways to solve them are given. One of the most important unresolved tasks is the task of recognizing the gestures of the deaf. To effectively solve it, an approach based on the development of bio-inspired neural networks is proposed. The architecture of a bio-inspired neural network, including four types of neurons, is described. New simpler MT neuron model proposed.

UR - http://www.scopus.com/inward/record.url?scp=85096586878&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1661/1/012038

DO - 10.1088/1742-6596/1661/1/012038

M3 - Conference article

AN - SCOPUS:85096586878

VL - 1661

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012038

T2 - 2020 International Conference on Information Technology in Business and Industry, ITBI 2020

Y2 - 6 April 2020 through 8 April 2020

ER -

ID: 27123055