MMGANGuard: A Robust Approach for Detecting Fake Images Generated by GANs Using Multi-Model Techniques-Reference-Cited by-同舟云学术

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MMGANGuard: A Robust Approach for Detecting Fake Images Generated by GANs Using Multi-Model Techniques

Published:2024 Issue: Volume:12 Page:104153-104164
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ali Raza Syed¹^ORCID,Habib Usman¹^ORCID,Usman Muhammad²^ORCID,Ashraf Cheema Adeel²^ORCID,Sajid Khan Muhammad³^ORCID

Affiliation:

1. FAST School of Computing, National University of Computer and Emerging Sciences, Islamabad, Pakistan

2. Department of Computer Science, National University of Computer and Emerging Sciences, Chiniot-Faisalabad Campus, Chiniot, Islamabad, Pakistan

3. Wales Institute of Digital Information, University of South Wales, Pontypridd, U.K.

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10508385.pdf?arnumber=10508385

Reference34 articles.

1. Deepfakes generation and detection: state-of-the-art, open challenges, countermeasures, and way forward

2. A brief introduction to artificial intelligence

3. The Effect of Deep Learning Methods on Deepfake Audio Detection for Digital Investigation

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