Classifying Real and AI-Generated Images Using Fine-Tuned ResNet50
Due to advancements in technology, especially in Artificial Intelligence, it has become increasingly difficult for humans to distinguish between real and AI-generated images. Technologies like Generative Adversarial Networks (GANs) and Latent Diffusion Models (LDMs) can generate images so realistic that humans often cannot identify them as AI-generated. This paper addresses the challenge of identifying AI-generated and real images by presenting a Fine-Tuned ResNet50 model. The model is trained and tested ona dataset of 140K real and fake face images, demonstrating its effectiveness in image classification.
Authors
- Khan Aabid Abdal Mashkoor
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.56147/aaiet.1.2.7
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00