The course focuses on "AI+Culture" and systematically introduces artificial intelligence, big language models, multimodal technologies, and cultural computing methods. Through cases such as Chinese painting, cultural heritage, archaeology, ancient architecture, and mural restoration, it demonstrates how artificial intelligence can participate in the digitization, analysis, protection, display, and innovation of cultural resources. Learners will understand the basic process of cultural data collection, processing, modeling, and visualization expression, and develop preliminary abilities to design intelligent application solutions for real cultural scenarios. At the same time, they will focus on the authenticity of generated content, cultural data security, and artificial intelligence ethics, deepening their understanding of Chinese culture in technical learning.
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Syllabus
- Chapter 1 Fundamentals of Artificial Intelligence(人工智能基础)
- 1.1 Artificial Intelligence Introduction(人工智能简介)
- 1.2 Classical Technologies(经典技术)
- 1.3 Advanced Technologies(前沿技术)
- 1.4 Huawei AI Framework(华为AI框架)
- 1.5 AI Data Foundation(AI数据基础)
- Chapter 2 Large Language Model(大语言模型)
- 2.1 Basic Knowledge of LLM(LLM基础知识)
- 2.2 Advanced Usage of LLM(LLM高级应用)
- 2.3 MindSpore Application(MindSpore应用实践)
- Chapter 3 Computational Culture(文化计算)
- 3.1 Concept of Cultural Computing(文化计算概念)
- 3.2 Cultural Heritage Preservation(文化遗产保护)
- 3.3 Cultural Data Visualization(文化数据可视化)
- 3.4 Image and Film Design(图像与影视设计)
- 3.5 Visual Art Creation(视觉艺术创作)
- Chapter 4 Computational Chinese Painting(中国绘画计算)
- 4.1 Materials & Tools of Chinese Painting(中国画的材料与工具)
- 4.2 Subjects and Techniques in Chinese Painting(中国画题材与技法)
- 4.3 Techniques Details & Painter dentities in Chinese Painting(中国画技法与画家)
- 4.4 The Evolution of Traditional Chinese Painting(中国传统绘画演变)
- 4.5 Traditional Ways of Viewing Chinese Painting & Curatorial Strategies(中国画观赏与策展)
- 4.6 Digital Technologies in Exhibition Design
- Chapter 5 Computational Cultural Heritage(文化遗产计算)
- 5.1 AI and Cultural Heritage(AI与文化遗产)
- 5.2 High-Fidelity Digitization(高保真数字化)
- 5.3 Intelligent Heritage Management(遗产智能管理)
- 5.4 Active Monitoring & Detection(智能监测与检测)
- 5.5 Virtual Restoration & Immersion(虚拟修复与沉浸体验)
- Chapter 6 Computational Archaeology(考古计算)
- 6.1 Field Archaeology Concept(田野考古概述)
- 6.2 Field Archaeology Review(田野考古调研)
- 6.3 Archaeological Remote Sensing(考古遥感基础)
- 6.4 Archaeology Image Segmentation(考古图像分割现状)
- Chapter 7 Computational Architecture(建筑计算)
- 7.1 Cultural Foundation of Chinese Architecture(中国建筑文化)
- 7.2 The Spread of Chinese Architectural Culture(建筑文化传播)
- 7.3 The Basic Characteristics of Chinese Architecture(中国建筑特征)
- 7.4 Types of Chinese Architectural Heritage(建筑遗产类型)
- 7.5 Development of Chinese Architectural Heritage(建筑遗产发展)
- 7.6 Traditional Techniques for Architectural Heritage Conservation(传统建筑遗产保护技术)
- 7.7 Intelligent Techniques for Architectural Heritage Conservation(智能建筑遗产保护技术)
- Chapter 8 Practical AI for Archaeological Remote Sensing Segmentation(智能考古遥感分割实践)
- 8.1 Archaeological AI Foundations(考古AI基础)
- 8.2 Archaeological Remote Sensing(考古遥感技术)
- 8.3 Archaeological Data Processing(考古数据处理)
- 8.4 Archaeological AI Models & Toolkits(AI模型与工具)
- 8.5 Archaeological Workflow & Applications(工作流程与应用)
- Chapter 9 Practical AI for Mural Restoration(智能壁画修复实践)
- 9.1 Mural Restoration(壁画修复基础)
- 9.2 CycleGAN model(CycleGAN模型)
- 9.3 Implementation in MindSpore(MindSpore实现)
- 9.4 Training and Visualization(模型训练与可视化)
- Final Exam
Taught by
Xu Chaoqing, Wei Zhang, and Zhu Wei