DeepFake Videos Detection by Using Recurrent Neural Network (RNN)

Author:

Albazony Ali Abdulzahra Mohsin1,Al-Wzwazy Haider A2,Al-Khaleefa Ahmed Salih3,Alazzawi Murtadha A.4,Almohamadi Mohammed5,Alavi Seyed Enayatallah1

Affiliation:

1. Faculty of Engineering Shahid Chamran University of Ahvaz,Computer Engineering Department,Ahvaz,Iran

2. Halfaya Oilfield Division Missan Oil Company,Maysan,Iraq

3. Faculty of Education University of Misan,Department of Physics,Maysan,Iraq

4. Imam Al-Kadhum College (IKC),Department of Computer Techniques Engineering,Baghdad,Iraq

5. College of Information Technology Imam Ja’afar Al-Sadiq University,Department of Computer Technical Engineering,Al-Muthanna,Iraq

Publisher

IEEE

Reference16 articles.

1. A convolutional LSTM based residual network for deepFake video detection;tariq;arXiv preprint arXiv 2009 07151,2020

2. Knowledge preserving OSELM model for Wi-Fi-based indoor localization;al-khaleefa;SENSORS,2019

3. MFA-OSELM Algorithm for WiFi-Based Indoor Positioning System

4. Deep Learning Algorithms for Arabic Handwriting Recognition: A Review

5. DeepFake video detection using convolutional vision transformer;wodajo;arXiv preprint arXiv 2102 11811,2021

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