Deep Fake Video Detection Using Transfer Learning Resnet50
Year: 2025
Type: article
Abstract: The rapid development of deep learning technologies has enabled the creation of highly realistic deepfake videos, raising concerns in areas such as media integrity, privacy, and security. Detecting these deepfakes has become a significant challenge, as conventional methods struggle to keep pace with increasingly sophisticated techniques. This journal explores the application of transfer learning using ResNet50, a pre-trained convolutional neural network, for deepfake video detection. We present an overview of deepfake creation, the role of ResNet50 in transfer learning, the implementation process, and the results of using this approach to detect deepfakes in video content.
Authors: S. Praveena, R.Kaviya, K.Sheerin Farhana, S.Bhuvanasri
Institution: Sri Manakula Vinayagar Educational Trust
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408738551