Understanding the Impact of Deep Learning Models on Building Information Modeling Systems: a Study on Generative Artificial Intelligence Tools †

dc.contributor.author Yönder,V.M.
dc.date.accessioned 2024-09-24T15:55:55Z
dc.date.available 2024-09-24T15:55:55Z
dc.date.issued 2023
dc.description.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. en_US
dc.identifier.doi 10.3390/IOCBD2023-15381
dc.identifier.issn 2673-4591
dc.identifier.scopus 2-s2.0-85197265976
dc.identifier.uri https://doi.org/10.3390/IOCBD2023-15381
dc.identifier.uri https://hdl.handle.net/11147/14803
dc.language.iso en en_US
dc.publisher Multidisciplinary Digital Publishing Institute (MDPI) en_US
dc.relation.ispartof Engineering Proceedings en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject bibliometric analysis en_US
dc.subject BIM designer en_US
dc.subject deep neural networks en_US
dc.subject generative artificial intelligence (GenAI/GAI) en_US
dc.subject text-to-image models en_US
dc.title Understanding the Impact of Deep Learning Models on Building Information Modeling Systems: a Study on Generative Artificial Intelligence Tools † en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Yönder,V.M.
gdc.author.scopusid 58612439800
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C5
gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.department Izmir Institute of Technology en_US
gdc.description.departmenttemp Yönder V.M., Architecture Faculty, Izmir Institute of Technology, Gülbahçe Campus, Izmir, 35433, Turkey en_US
gdc.description.issue 1 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q4
gdc.description.volume 53 en_US
gdc.description.wosquality N/A
gdc.identifier.openalex W4392478894
gdc.index.type Scopus
gdc.oaire.accesstype GOLD
gdc.oaire.diamondjournal false
gdc.oaire.impulse 1.0
gdc.oaire.influence 2.6459237E-9
gdc.oaire.isgreen false
gdc.oaire.keywords text-to-image models
gdc.oaire.keywords Engineering machinery, tools, and implements
gdc.oaire.keywords bibliometric analysis
gdc.oaire.keywords deep neural networks
gdc.oaire.keywords BIM designer
gdc.oaire.keywords generative artificial intelligence (GenAI/GAI)
gdc.oaire.keywords TA213-215
gdc.oaire.popularity 3.5106145E-9
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0209 industrial biotechnology
gdc.oaire.sciencefields 0211 other engineering and technologies
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration National
gdc.openalex.fwci 0.42841654
gdc.openalex.normalizedpercentile 0.59
gdc.opencitations.count 0
gdc.plumx.crossrefcites 1
gdc.plumx.mendeley 35
gdc.plumx.newscount 1
gdc.plumx.scopuscites 0
gdc.scopus.citedcount 0
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relation.isOrgUnitOfPublication.latestForDiscovery 9af2b05f-28ac-4003-8abe-a4dfe192da5e

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