Practical Evaluation and Performance Analysis for Deepfake Detection Using Advanced AI Models
Year: 2025
Type: conference-paper
Abstract: In the 21st century of digital technology, deepfakes are increasingly becoming a serious issue across the globe. We have many machine learning and deep learning algorithms that are meant to serve humanity, but nowadays, these algorithms are the main cause of deepfake media, which can affect human life. This study aimed to create a model for recognizing deepfake media or manipulated media using deep learning and machine learning algorithms. The dataset we required for training the model was collected from online sources, and we created some GAN-generated images. Then, we created a model by using the MTCNN, InceptionResNetV1, and FaceNet_PyTorch. All the algorithms gave an excellent result, with an accuracy of 95% by the MTCNN, 98% by InceptionResNetV1, and 98% by Facenet_pytorch.
Authors: Bikash Ranjan Barik, Ankush Nayak, Adyasha Biswal, Neelamadhab Padhy
Institution: GIET University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4409145511