Research on Innovative Design of Miao Painting in Xiangxi Based on Generative Artificial Intelligence
- DOI
- 10.2991/978-2-38476-511-9_89How to use a DOI?
- Keywords
- Miao painting in western Hunan; generative image; innovative design; cultural inheritance
- Abstract
This study leverages artificial intelligence-driven generative image technology to digitally classify, screen, and extract materials from Xiangxi Miao paintings, thereby constructing a digital resource repository for Miao paintings. Generative AI technologies such as generative technology, deep learning, and machine learning are employed to conduct digital innovative design analysis of Xiangxi Miao paintings. The aim is to establish a digital reproduction system for Xiangxi Miao paintings, promote the development and dissemination of the Xiangxi Miao painting cultural and creative design industry, contribute to the promotion of Hunan's excellent traditional culture, enhance public cultural identity and cohesion, enrich the spiritual and cultural lives of the people, and provide cultural support for the creation of the “Cultural Xiang Products” specialty brand, the advancement of the “Cultural Power Province” strategy, and the construction of a prosperous, beautiful, and happy new Hunan.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Ying He AU - Ping Wang PY - 2025 DA - 2025/12/31 TI - Research on Innovative Design of Miao Painting in Xiangxi Based on Generative Artificial Intelligence BT - Proceedings of the 7th International Conference on Literature, Art and Human Development (ICLAHD 2025) PB - Atlantis Press SP - 774 EP - 780 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-511-9_89 DO - 10.2991/978-2-38476-511-9_89 ID - He2025 ER -