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DeepFake Detection Algorithms: A Meta-Analysis

Published: 17 December 2020 Publication History

Abstract

We analyzed the developed methods of computer vision in areas associated with recognition and detection of DeepFakes using various models and architectures of neural networks: mainly GAN and CNN. We also discussed the main types and models of these networks that are most effective in detecting and recognizing objects from different data sets, which were provided in the studied articles.

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Cited By

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  • (2024)Diverse misinformation: impacts of human biases on detection of deepfakes on networksnpj Complexity10.1038/s44260-024-00006-y1:1Online publication date: 18-May-2024
  • (2024)Unmasking deepfakes: A systematic review of deepfake detection and generation techniques using artificial intelligenceExpert Systems with Applications10.1016/j.eswa.2024.124260252(124260)Online publication date: Oct-2024
  • (2024)Deepfake video detection: challenges and opportunitiesArtificial Intelligence Review10.1007/s10462-024-10810-657:6Online publication date: 29-May-2024
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cover image ACM Other conferences
SSPS '20: Proceedings of the 2020 2nd Symposium on Signal Processing Systems
July 2020
125 pages
ISBN:9781450388627
DOI:10.1145/3421515
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 17 December 2020

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Author Tags

  1. CNN
  2. Computer vision
  3. DeepFake
  4. Face detection GAN

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View all
  • (2024)Diverse misinformation: impacts of human biases on detection of deepfakes on networksnpj Complexity10.1038/s44260-024-00006-y1:1Online publication date: 18-May-2024
  • (2024)Unmasking deepfakes: A systematic review of deepfake detection and generation techniques using artificial intelligenceExpert Systems with Applications10.1016/j.eswa.2024.124260252(124260)Online publication date: Oct-2024
  • (2024)Deepfake video detection: challenges and opportunitiesArtificial Intelligence Review10.1007/s10462-024-10810-657:6Online publication date: 29-May-2024
  • (2023)Deepfakes: Deceptions, mitigations, and opportunitiesJournal of Business Research10.1016/j.jbusres.2022.113368154(113368)Online publication date: Jan-2023
  • (2023)Deepfakes: evolution and trendsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08605-y27:16(11295-11318)Online publication date: 15-Jun-2023
  • (2021)Использование искусственного интеллекта в преступных целях: уголовно-правовая характеристикаАзиатско-Тихоокеанский регион: экономика, политика, право10.24866/1813-3274/2021-3/153-16560:3(153-165)Online publication date: 2021

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