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FRiS-censoring of reference sample in face recognition task by deep neural networks. / Alyamkin, Sergey A.; Nikolenko, Nikita A.; Pavlovskiy, Evgeniy N. et al.

Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 41-43 8071961.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Alyamkin, SA, Nikolenko, NA, Pavlovskiy, EN & Dyubanov, VV 2017, FRiS-censoring of reference sample in face recognition task by deep neural networks. in Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017., 8071961, Institute of Electrical and Electronics Engineers Inc., pp. 41-43, 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017, Novosibirsk, Akademgorodok, Russian Federation, 12.04.2017. https://doi.org/10.1109/SSDSE.2017.8071961

APA

Alyamkin, S. A., Nikolenko, N. A., Pavlovskiy, E. N., & Dyubanov, V. V. (2017). FRiS-censoring of reference sample in face recognition task by deep neural networks. In Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 (pp. 41-43). [8071961] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSDSE.2017.8071961

Vancouver

Alyamkin SA, Nikolenko NA, Pavlovskiy EN, Dyubanov VV. FRiS-censoring of reference sample in face recognition task by deep neural networks. In Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 41-43. 8071961 doi: 10.1109/SSDSE.2017.8071961

Author

Alyamkin, Sergey A. ; Nikolenko, Nikita A. ; Pavlovskiy, Evgeniy N. et al. / FRiS-censoring of reference sample in face recognition task by deep neural networks. Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 41-43

BibTeX

@inproceedings{81d4cdc34e6b476e8b411700eb5d35dc,
title = "FRiS-censoring of reference sample in face recognition task by deep neural networks",
abstract = "To increase face recognition quality in video surveillance system an approach of censoring incoming photos based on FRiS function is presented.",
keywords = "censoring, convolution neural net-work, face recognition, FRiS",
author = "Alyamkin, {Sergey A.} and Nikolenko, {Nikita A.} and Pavlovskiy, {Evgeniy N.} and Dyubanov, {Vladimir V.}",
year = "2017",
month = oct,
day = "18",
doi = "10.1109/SSDSE.2017.8071961",
language = "English",
pages = "41--43",
booktitle = "Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
note = "2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 ; Conference date: 12-04-2017 Through 13-04-2017",

}

RIS

TY - GEN

T1 - FRiS-censoring of reference sample in face recognition task by deep neural networks

AU - Alyamkin, Sergey A.

AU - Nikolenko, Nikita A.

AU - Pavlovskiy, Evgeniy N.

AU - Dyubanov, Vladimir V.

PY - 2017/10/18

Y1 - 2017/10/18

N2 - To increase face recognition quality in video surveillance system an approach of censoring incoming photos based on FRiS function is presented.

AB - To increase face recognition quality in video surveillance system an approach of censoring incoming photos based on FRiS function is presented.

KW - censoring

KW - convolution neural net-work

KW - face recognition

KW - FRiS

UR - http://www.scopus.com/inward/record.url?scp=85040378084&partnerID=8YFLogxK

UR - https://elibrary.ru/item.asp?id=35531523

U2 - 10.1109/SSDSE.2017.8071961

DO - 10.1109/SSDSE.2017.8071961

M3 - Conference contribution

AN - SCOPUS:85040378084

SP - 41

EP - 43

BT - Proceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017

Y2 - 12 April 2017 through 13 April 2017

ER -

ID: 9642080