Imaginary Vessels: Machine Learning digital dataset creation for robotic pottery fabrication

Cami Quinteros, Hesham Shawqy, Gabriella Rossi, Iliana Papadopoulou, David Leon

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

Originalsprog	Engelsk
Titel	Realignments: Towards Critcal Computation : Proceedings of the 41st Annual Conference of the Association for Computer Aided Design in Architecture
Antal sider	10
Publikationsdato	2022
Sider	142-151
ISBN (Trykt)	979-8986080567
Status	Udgivet - 2022

Kunstnerisk udviklingsvirksomhed (KUV)

Quinteros, C., Shawqy, H., Rossi, G., Papadopoulou, I., & Leon, D. (2022). Imaginary Vessels: Machine Learning digital dataset creation for robotic pottery fabrication. I Realignments: Towards Critcal Computation: Proceedings of the 41st Annual Conference of the Association for Computer Aided Design in Architecture (s. 142-151) http://acadia.org/content/conferences#past_conferences

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title = "Imaginary Vessels: Machine Learning digital dataset creation for robotic pottery fabrication",

author = "Cami Quinteros and Hesham Shawqy and Gabriella Rossi and Iliana Papadopoulou and David Leon",

year = "2022",

language = "English",

isbn = "979-8986080567",

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Quinteros, C, Shawqy, H, Rossi, G, Papadopoulou, I & Leon, D 2022, Imaginary Vessels: Machine Learning digital dataset creation for robotic pottery fabrication. i Realignments: Towards Critcal Computation: Proceedings of the 41st Annual Conference of the Association for Computer Aided Design in Architecture. s. 142-151. <http://acadia.org/content/conferences#past_conferences>

Imaginary Vessels: Machine Learning digital dataset creation for robotic pottery fabrication. / Quinteros, Cami; Shawqy, Hesham; Rossi, Gabriella et al.
Realignments: Towards Critcal Computation: Proceedings of the 41st Annual Conference of the Association for Computer Aided Design in Architecture. 2022. s. 142-151.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review