Використання методів ші для генерування різноманітних образів

Abstract

Artificial intelligence is increasingly penetrating various areas of our lives. AI for image generation uses neural networks to create realistic and unique visual materials. Modern approaches, such as Generative Adversarial Networks (GAN), Variational Autoencoders (VAE), and Diffusion Models, allow generating high-quality images used in art, design, cinema, and scientific research. One of the most effective models is Stable Diffusion, which provides flexibility, control over generation parameters, and high-quality results, making the technology accessible to a wide range of users.