Year: 2024
Type: article
Abstract: Deepfake Detection: A Convolutional Neural Network Approach Digital authenticity is in grave danger due to the rapid advancement of deepfake technology.This research introduces a robust deep learning-based method to accurately detect deepfakeimages. A CNN (convolutional neural network) architecture is developed and trained on a diverse dataset of authentic and manipulated images. CNN model effectively learns discriminative features, enabling it to distinguish between genuine and forged content. The model's superior performance in identifying different deepfake techniques is demonstrated by experimental results, underscoring its potential to prevent the spread of false informationand protect digital integrity
Author: Shubham Pal Singh
Institution: Birla Institute of Technology and Science, Pilani
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404118859