Research on the application of data enhancement and image restoration based on Generative Adversarial Network (GAN)

Generative adversarial network GAN can generate high-quality synthetic data through the adversarial training of generator and discriminator, so as to provide diversified training samples in data enhancement and image restoration, and improve the generalization ability of the model, which makes it have excellent performance in dealing with various tasks and can output high-quality data and pictures. Starting from the basic principles and main variants of GAN, this paper analyzes in detail the application cases, effect evaluation and challenges of GAN in data enhancement and image restoration, and looks forward to the future development direction of GAN.