Research on digital art generation and cultural identity based on deep learning algorithms

In order to explore the application of deep learning technology in digital art creation, this study uses Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Style Transfer techniques to analyze their ability to imitate and innovate artistic styles and their impact on cultural identity. The results indicate that these models can effectively generate images with high artistic and cultural expression, providing a new perspective for the integration of art and technology in the future.