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Artificial Intelligence and Decision Making, 2022, Issue 2, Pages 62–73
DOI: https://doi.org/10.14357/20718594220206 (Mi iipr65) 		 
This article is cited in 1 scientific paper (total in 1 paper)

Machine learning, neural networks

Method for deepfake detection using convolutional neural networks

S. S. Volkova

Vologda State University, Vologda, Russia
Full-text PDF (880 kB) Citations (1)
DOI: https://doi.org/10.14357/20718594220206
Abstract: The article proposed the face anti-digital-spoofing countermeasures method for improving the protection of the facial biometric system. The DeepFake detection method is based on the convolutional neural networks, trained on a large dataset that contains different fake types with different qualities. This has resulted in at least 99% of detection quality. The suggested method can be used to increase the protection of facial biometric systems by reducing the risk of unauthorized access.
Keywords: biometric authentication, spoofing, DeepFake, convolutional neural network, recognition.
Funding agency Grant number
Governments of the Vologda region
English version:
Scientific and Technical Information Processing, 2023, Volume 50, Issue 5, Pages 475–485
DOI: https://doi.org/10.3103/S0147688223050143
Bibliographic databases:
Document Type: Article
Language: Russian
Citation: S. S. Volkova, “Method for deepfake detection using convolutional neural networks”, Artificial Intelligence and Decision Making, 2022, no. 2, 62–73; Scientific and Technical Information Processing, 50:5 (2023), 475–485
Citation in format AMSBIB
\Bibitem{Vol22}
\by S.~S.~Volkova
\paper Method for deepfake detection using convolutional neural networks
\jour Artificial Intelligence and Decision Making
\yr 2022
\issue 2
\pages 62--73
\mathnet{http://mi.mathnet.ru/iipr65}
\crossref{https://doi.org/10.14357/20718594220206}
\elib{https://elibrary.ru/item.asp?id=48707186}
\transl
\jour Scientific and Technical Information Processing
\yr 2023
\vol 50
\issue 5
\pages 475--485
\crossref{https://doi.org/10.3103/S0147688223050143}
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  • https://www.mathnet.ru/eng/iipr/y2022/i2/p62
    • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Artificial Intelligence and Decision Making
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    Full-text PDF :19
     
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