The role of deep neural network in the creation of traditional Chinese landscape painting.

With the wide application of deep learning technology in various fields, its potential in artistic creation has gradually attracted attention. This research focuses on the application of deep learning in the creation of traditional Chinese landscape painting and its cultural and aesthetic impact. First, the research comprehensively analyzes the existing deep learning algorithms and the basic elements of Chinese landscape painting to determine the most suitable model architecture. Then, through several rounds of experiments, various training parameters are adjusted and the optimal network configuration is determined. In terms of assessment, the study uses a variety of indicators, including visual quality and technical performance, as well as in-depth cultural and aesthetic analysis. The results show that deep learning not only effectively improves visual quality and technical performance, but also has a positive impact on culture and aesthetics. Although there are some limitations, such as high computational requirements and reliance on large amounts of training data, corresponding solutions are also proposed. This study provides a powerful experimental basis for the integration of Chinese traditional art and modern science and technology, and promotes the research in this field. [ABSTRACT FROM AUTHOR]