| id |
acadia22_662 |
| authors |
Furgiuele, Antonio; Ergezer, Mehmet; Zaman, Cagri Hakan |
| year |
2022 |
| title |
Towards an Adversarial Architecture |
| 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. 662-671. |
| summary |
A key technological weakness of artificial intelligence (AI) is adversarial images, a constructed form of image-noise added to an image that can manipulate machine learning algorithms but is imperceptible to humans. Adversarial Architecture explores the application of adversarial images to the built environment and develops a new method of design agency to directly engage artificial intelligence. Embedding a layer of information to physical surfaces that is only perceptible to machines has many potential applications, such as uniquely identifying and tracking objects, embedding accessibility features directly to surfaces, and counter-surveillance systems in different scales. |
| series |
ACADIA |
| type |
paper |
| email |
|
| full text |
 file.pdf (3,285,128 bytes) |
| references |
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Alexey Bochkovsky, C. Hon-Yuan Yan (2021)
 Traffic Sign Detection using YOLOv4”
, International Journal of Creative Research Thoughts 9(5): 891–897
|
|
|
|
|
Alexey Kurakin, Ian Goodfellow, and Samy Bengio (2016)
Adversarial examples in the physical world
, Technical Report, Google, Inc. arXiv: 1607.02533v1
|
|
|
|
|
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus (2013)
Intriguing properties of neural networks
, arXiv preprint arXiv: 1312.6199
|
|
|
|
|
Ian J. Goodfellow, Jonathon Shlens, and Christian Szegedy (2014)
Explaining and harnessing adversarial examples
, arXiv preprintarXiv: 1412.6572
|
|
|
|
|
Joseph Redmon, and Ali Farhadi (2018)
Yolov3: An Incremental Improvement
, arXiv preprint arXiv: 1804.02767
|
|
|
|
|
Joseph Redmon, Santosh Divvala, Ross Girshick, and Ali Farhadi (2016)
You Only Look Once: Unified, Real-Time Object Detection
, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 779–788
|
|
|
|
|
Karen Simonyan, and Andrew Zisserman (2014)
Very deep convolu- tional networks for large-scale image recognition
, arXiv preprintarXiv: 1409.1556 (2014).
|
|
|
|
|
M. Callon, M. Akrich, B. Latour, J. Law (2001)
Actor-Network Theory
, International Encyclopedia of the Social & Behavioral Sciences, Amsterdam: Elsevier. 62–66
|
|
|
|
|
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen (2018)
Mobilenetv2: Inverted Residuals and Linear Bottlenecks
, 2018 IEEE/CVF Conference on Computer Vision andPattern Recognition. 4510–4520
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| last changed |
2024/02/06 14:04 |
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