SYNTHETIC DATA GENERATION PIPELINE FOR GEOMETRIC DEEP LEARNING IN ARCHITECTURE

Autor: Amirhossein Ahmadnia, Jiayao Zhang, Cecilia Maria Bolognesi, Meher Shashwat Nigam, Dominik L. Michels, Alberto Tono, Stanislava Fedorova

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B2-2021, Pp 337-344 (2021)

With the growing interest in deep learning algorithms and computational design in the architectural field, the need for large, accessible and diverse architectural datasets increases. Due to the complexity of such 3D datasets, the most widespread tec

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::222129bdb6a79e43734a6da7e11e6070
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B2-2021/337/2021/isprs-archives-XLIII-B2-2021-337-2021.pdf

Encoded Memory

Autor: Hannah Tono, Alberto Tono, Andrea Zani

This chapter provides an overview of some artificial intelligence applications in the architecture, engineering, and construction industry. Furthermore, the authors will define Creativity and its limits for the machine in the role of architecture. Th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c9a7e70b899b0f0563230b57e262b1f6
https://doi.org/10.4018/978-1-7998-1234-0.ch012