ArcGAN

The project involves developing a Generative Adversarial Network (GAN) to create high-quality synthetic data. The GAN consists of two neural networks: a Generator, which produces realistic data samples, and a Discriminator, which evaluates and differentiates between real and generated data. The system is trained through a competitive process where the Generator improves its outputs to deceive the Discriminator, while the Discriminator enhances its ability to detect fakes. The result is a powerful tool for generating realistic architectural designs with structural integrity and also useful in applications like image enhancement, data augmentation, and creative content generation.