| id |
caadria2023_24 |
| authors |
Yin, Xiang |
| year |
2023 |
| title |
AI and Typology |
| doi |
https://doi.org/10.52842/conf.caadria.2023.1.039
|
| source |
Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 39–48 |
| summary |
The paper discusses a novel design approach that applies artificial intelligence as an auxiliary tool throughout typology research and architectural design. The method attempts to utilize neural network as a research tool to detect and identify features of a typical architectural type within the specific society context and demonstrate its potential for regional design under the theme of human centric. Typology classification, computational vision, and human-machine collaboration are entwined throughout machine learning and architectural design. The paper aims to demonstrate the ability of 3D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutions (TreeGAN) to study the inherent principle and characteristic of an architectural type and its potential to provide possible design inspirations based on the typological formation principles concluded by Deep Learning. The article exhibits the key result generated by TreeGAN in a specific architecture type—churches, as the prototype of a design method and conducts a project in Manhattan. |
| keywords |
Architecture Typology, Artificial Intelligence, Machine Learning, TreeGAN, Human-machine Collaboration |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (2,144,173 bytes) |
| references |
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| last changed |
2023/06/15 23:14 |
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