Enhanced Deepfake Detection Using Preprocessed Video Frames And Convolution Neural Networks

• Author(s):

  R.Mohana Brintha | R. Pavithra | A. Alagar

• Keywords:

  Deepfake Detection, Convolutional Neural Network (CNN), Video Analysis, Machine Learning, Deep Learning, Face Recognition, Image Preprocessing, Artificial Intelligence, Feature Extraction, Classification, Gradio Interface, Model Prediction, Frame Processi

• Abstract:

  Digital Security And Authenticity Are Being Threatened By Deepfake Technology, Which Is Powered By Sophisticated Generative Models. A Convolutional Neural Network (CNN) Model Trained On Facial Data Taken From Video Frames Is Used In This Study To Demonstrate A Deep Learning-based Method For Identifying Deepfake Films. Prior To Classification, The System Preprocesses Video Data By Normalizing And Shrinking Frames. Real-time Video Uploading And Prediction Are Made Possible By A Gradio-based User Interface, Which Indicates The Likelihood Of Authentic Or Fraudulent Footage. The Model's Ability To Counteract Synthetic Media And Guarantee Trust In Visual Content Across Digital Communication Channels Is Highlighted By Experimental Results That Show Dependable Detection Performance.

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Other Details

• Paper id:

  IJSARTV11I10104179

• Published in:

  Volume: 11 Issue: 10 October 2025

• Publication Date:

  2025-10-24

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