Deep-Fake Detection Using Deep Learning
Year: 2025
Type: article
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.
Authors: Nagashree K T, Shristi, Sania Firdaushi, Shweta B Patil, Shristi Singh
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W6893201978
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