Enhancing Trust in the Digital Age: Deepfake Detection with Xception Binary Classifier
Paper Key : IRJ************691
Author: Akash Kiran Chavan,Tanay Sujit Dajgude,Kumar Arun Kad
Date Published: 06 Nov 2023
Deepfake technology has drawn a lot of interest because of its potential for malevolent usage in the dissemination offalse and misleading information. In response, this research introduces an innovative method that uses an XceptionBinary Classifier to identify deepfake films. This architecture, called Xception, is well-known for its ability to doimage classification tasks. It is modified for binary classification, which separates real films from deepfake videos.The methodology, data collecting, and analysis are described in depth in this work, which also demonstrates theeffectiveness of our approach in detecting deepfakes and so contributes to the ongoing attempts to counter this newthreat.