DeepFakeDG: A Deep Learning Approach for Deep Fake Detection and Generation
Last updated: 24 Dec 2024
10.21608/jocc.2023.307056
neural machine translation, Sequence to Sequence Model, Sign Language, Deep learning, Transformer
Diaa
AbdElminaam
s
Department of Data Science , Faculty of Computer Science , Misr International University , Cairo , Egypt
diaa.salama@miuegypt.edu.eg
0000-0002-1544-9906
Natalie
Sherif
Faculty of computer science ; Misr International University
natalie1901991@miuegypt.edu.eg
cairo
zeina
Ayman
Faculty of computer science ; Misr International University
zeina1900600@miuegypt.edu.eg
cairo
Mariam
Mohamed
Faculty of computer science ; Misr International University
mariam1901474@miuegypt.edu.eg
cairo
Mohamed
Hazem
Faculty of computer science ; Misr International University
mohamed02155@miuegypt.edu.eg
cairo
2
2
42348
2023-07-01
2023-05-27
2023-07-01
31
37
2636-3577
https://jocc.journals.ekb.eg/article_307056.html
https://jocc.journals.ekb.eg/service?article_code=307056
4
Original Article
731
Journal
Journal of Computing and Communication
https://jocc.journals.ekb.eg/
DeepFakeDG: A Deep Learning Approach for Deep Fake Detection and Generation
Details
Type
Article
Created At
24 Dec 2024