Deep-Fake Detection Using Deep Learning

Deep-Fake Detection is a new technology which has caught extreme fashionability in the present generation. Deep-Fake has now held serious pitfalls over spreading misinformation to the world, destroying political faces and also blackmailing individualities to prize centrals. As this technology has taken over the internet in a veritably short span of time and also numerous readily apps are also available to execute Deep-Fake contents, and numerous of the individualities has made systems grounded on detecting the deepfake contents whether it’s fake or real. From the DL(deep learning) – grounded approach good results can be attained, this paper presents substantially the results of our current study which is indicating the traditional machine learning (ML) fashion. This projects points in discovery of video tape deepfakes using deep literacy ways like ResNext and LSTM. We've achived deepfake discovery by using transfer literacy where the pretrained ResNext CNN is used to gain a point vector, further the LSTM subcaste is trained using the features.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-05
DOI
https://doi.org/10.5281/zenodo.14808072
Primary Topic
Generative Adversarial Networks and Image Synthesis
Type
article
Field-Weighted Citation Impact
0.00
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article

Deep-Fake Detection Using Deep Learning

Zenodo (CERN European Organization for Nuclear Research)
Generative Adversarial Networks and Image Synthesis
article

Deep-Fake Detection Using Deep Learning

article en

Abstract

Deep-Fake Detection is a new technology which has caught extreme fashionability in the present generation. Deep-Fake has now held serious pitfalls over spreading misinformation to the world, destroying political faces and also blackmailing individualities to prize centrals. As this technology has taken over the internet in a veritably short span of time and also numerous readily apps are also available to execute Deep-Fake contents, and numerous of the individualities has made systems grounded on detecting the deepfake contents whether it’s fake or real. From the DL(deep learning) – grounded approach good results can be attained, this paper presents substantially the results of our current study which is indicating the traditional machine learning (ML) fashion. This projects points in discovery of video tape deepfakes using deep literacy ways like ResNext and LSTM. We've achived deepfake discovery by using transfer literacy where the pretrained ResNext CNN is used to gain a point vector, further the LSTM subcaste is trained using the features.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 52%
Generative Adversarial Networks and Image Synthesis
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