Authors : Nagashree K T; Shristi; Sania Firdaushi; Shweta B Patil; Shristi Singh

Volume/Issue : Volume 10 - 2025, Issue 1 - January

Google Scholar : https://tinyurl.com/yd85pvca

Scribd : https://tinyurl.com/2navffz2

DOI : https://doi.org/10.5281/zenodo.14808073

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.

Keywords : Detection, Deepfakes, Deep Learning, ResNext and LSTM.

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