| id |
acadia22_628 |
| authors |
Sung, Woongki; Nagakura, Takehiko; Tsai, Daniel |
| year |
2022 |
| title |
Design Contextualism by AI |
| 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. 628-637. |
| summary |
This paper presents a data- driven method for encoding and representing the statistical information of an architectural site layout in the form of a Bayesian network. Given a set of simplified satellite photos and maps, the site layout model is formulated that consists of variables of interest. Structured learning is performed to find an optimal Bayesian network structure that best fits the dataset and is then trained to calculate its parameters. |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (3,397,778 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/02/06 14:04 |
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