Deepfake Detection Using Deep Learning

Abstract

As deepfake technology rapidly advances, it’s becoming increasingly difficult to distinguish between authentic and altered digital media. This study explores the application of deep learning techniques, specifically convolutional neural networks (CNNs) and Transformer-based models, to effectively detect deepfakes. The study provides a detailed experimental evaluation of the performance of these models in recognizing manipulated facial images and videos.

In recent years, the rapid development of China's telecom industry has greatly improved the speed of telecom network construction. In addition, the telecom network (CNN) has also been used to learn the dynamics of Transformer, which has also been widely used. to make something happen.