| id |
acadia22_310 |
| authors |
Koehler, Daniel |
| year |
2022 |
| title |
Building Synthetic Data Sets or How to Learn from Future Architectures? |
| source |
ACADIA 2022: Hybrids and Haecceities [Proceedings of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 310-317. |
| summary |
Simulating synthetic data can induce design speculation to machine learning applications. Leaning on density studies for modernist settlements, we propose an approach that mixes ratios of sets to generate buildings quickly. A case study exemplifies how quickly one can generate and analyze a set of buildings at the resolution of BIM modeling. We conclude that synthetic data sets could become a feature of daily design workflows due to being computationally inexpensive and easy to adapt. |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (5,202,825 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/02/06 14:00 |
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