Generative Artificial Intelligence for image synthesis using Generative Adversarial Networks (GANs) and variational autoencoders
This research paper presents a comprehensive, end-to-end framework that addresses both generative synthesis and discriminative detection under hardware-constrained (CPU-only) environments, and presents a compact Convolutional Neural Network designed to detect and classify images as real or fake.