Deepfake Detection Using Deep Learning

Authors

  • Jayshri Mankar Professor, Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Pune, India
  • Shriyash Ingle Student, Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Pune, India
  • Tejas Dalvi Student, Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Pune, India
  • Abhishek Bhalerao Student, Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Pune, India
  • Manasi Pol Student, Department of Computer Engineering, Genba Sopanrao Moze College of Engineering, Pune, India

Keywords:

Deep Learning, Faceswap, DeepFake, DeepFake techniques

Abstract

Four billion images are uploaded to the internet every day, according to polls. With the widespread use of digital photography, new methods for modifying image content employing tools, apps, and editing software like Adobe's have emerged. Deepfake techniques were used to create a fake movie and photos, which has raised significant public concern. The majority of face-manipulation techniques used in videos today, such as Faceswap and Deepfake, have been created successfully. It has both benefits and drawbacks. On the one hand, it broadens the application to new fields (such as visual arts, visual studies, filmmaking, etc.), but on the other, it also fosters harmful users. Consequently, we can determine whether the video is real or not by applying Deep Learning algorithms. We're going to create a system that can identify this dangerous data in order to recognise it.

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Published

08-05-2023

Issue

Section

Articles

How to Cite

[1]
J. Mankar, S. Ingle, T. Dalvi, A. Bhalerao, and M. Pol, “Deepfake Detection Using Deep Learning”, IJMDES, vol. 2, no. 4, pp. 67–68, May 2023, Accessed: Jun. 13, 2024. [Online]. Available: https://journal.ijmdes.com/ijmdes/article/view/134