Localization of Facial Images Manipulation in Digital Forensics via Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Localization of Facial Images Manipulation in Digital Forensics via Convolutional Neural Networks

Published:2021 Issue: Volume: Page:313-325
ISSN:2524-7565
Container-title:Enabling Machine Learning Applications in Data Science
language:
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Author:

Mawgoud Ahmed A.^ORCID,Albusuny Amir^ORCID,Abu-Talleb Amr^ORCID,Tawfik Benbella S.^ORCID

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-33-6129-4_22

Reference23 articles.

1. Rahmouni N, Nozick V, Yamagishi J, Echizen I (2017) Distinguishing computer graphics from natural images using convolution neural networks. In: 2017 IEEE workshop on information forensics and security (WIFS). IEEE, pp 1–6

2. Mawgoud AA, Taha MH, Khalifa NE, Loey M (2020) Cyber security risks in MENA region: threats, challenges and countermeasures. In: International conference on advanced intelligent systems and informatics. Springer, Cham, pp 912–921

3. Gong D (2020) Deepfake forensics, an ai-synthesized detection with deep convolutional generative adversarial networks. Int J Adv Trends Comput Sci Eng 9:2861–2870. https://doi.org/10.30534/ijatcse/2020/58932020

4. Rossler A, Cozzolino D, Verdoliva L, Riess C, Thies J, Nießner M (2019) Faceforensics++: learning to detect manipulated facial images. In: Proceedings of the IEEE international conference on computer vision, pp 1–11

5. Kleinmann A, Wool A (2014) Accurate modeling of the siemens S7 SCADA protocol for intrusion detection and digital forensics. J Digit Foren Secur Law. https://doi.org/10.15394/jdfsl.2014.1169

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