Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/14803
Title: Understanding the Impact of Deep Learning Models on Building Information Modeling Systems: A Study on Generative Artificial Intelligence Tools †
Authors: Yönder,V.M.
Keywords: bibliometric analysis
BIM designer
deep neural networks
generative artificial intelligence (GenAI/GAI)
text-to-image models
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
Abstract: The power of the relationship between building information modeling (BIM) systems and advanced artificial intelligence models holds considerable weight for users of BIM. This relationship allows the generation, analysis, and deduction of insights from substantial construction digital data. This research explores the relationship between generative artificial intelligence (generative AI), deep neural nets, and the BIM systems, including its users. This study examines the correlation between generative artificial intelligence and BIM methodology by conducting a case study. Furthermore, this paper investigates the conceptual and practical use of generative AI components (e.g., text-to-image models, diffusion networks, deep neural networks, large language model, and generative adversarial network) in BIM systems via bibliometric analysis. © 2023 by the author.
URI: https://doi.org/10.3390/IOCBD2023-15381
https://hdl.handle.net/11147/14803
ISSN: 2673-4591
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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