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

Sergey A. Alyamkin, Nikita A. Nikolenko, Evgeniy N. Pavlovskiy, Vladimir V. Dyubanov

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

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

Original languageEnglish
Title of host publicationProceedings - 2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages41-43
Number of pages3
ISBN (Electronic)9781538615935
DOIs
Publication statusPublished - 18 Oct 2017
Event2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017 - Novosibirsk, Akademgorodok, Russian Federation
Duration: 12 Apr 201713 Apr 2017

Conference

Conference2017 Siberian Symposium on Data Science and Engineering, SSDSE 2017
CountryRussian Federation
CityNovosibirsk, Akademgorodok
Period12.04.201713.04.2017

Keywords

  • censoring
  • convolution neural net-work
  • face recognition
  • FRiS

OECD FOS+WOS

  • 1.02 COMPUTER AND INFORMATION SCIENCES

State classification of scientific and technological information

  • 27 MATHEMATICS

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