| id |
acadia22_224 |
| authors |
Coersmeier, Jonas; Nanasca, James; Man Hin, Ivan Yan; Blasetti, Ezio |
| year |
2022 |
| title |
Nanotectonica SEM-GAN |
| 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. 224-243. |
| summary |
The present study, Nanotectonica SEM-GAN, focuses on two processes for image production, one based in the field of nanotechnology and the other in machine learning: Scanning Electron Microscopy (SEM) and Generative Adversarial Networks (GAN). It establishes commonalities of these routines as they pertain to aesthetics and design methodology, and it explores methods of spatializing and materializing images produced in their interaction. The study of transposing rich image material to three-dimensional geometry and material artifact is considered relevant not only to the particular study at hand, but also to the general problem of image-based machine learning techniques when applied in the spatial design disciplines. A third process, Robotic Incremental Metal Forming (RIMF), advances the aesthetic language of SEM-GAN through the sculptural method of the relief. |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (20,633,164 bytes) |
| references |
Content-type: text/plain
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| last changed |
2024/02/06 14:00 |
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