Chapter Generative Design Intuition from the Fine-Tuned Models of Named Architects’ Style
dc.contributor.author | Jeong, Hyun | |
dc.contributor.author | Yoo, Youngjin | |
dc.contributor.author | Kim, Youngchae | |
dc.contributor.author | Cha, SeungHyun | |
dc.contributor.author | Lee, Jin-Kook | |
dc.date.accessioned | 2024-04-02T15:44:31Z | |
dc.date.available | 2024-04-02T15:44:31Z | |
dc.date.issued | 2023 | |
dc.identifier | ONIX_20240402_9791221502893_10 | |
dc.identifier.issn | 2704-5846 | |
dc.identifier.uri | https://library.oapen.org/handle/20.500.12657/89041 | |
dc.description.abstract | This paper suggests the potential application of generative artificial intelligence-based image generation technology in the field of architecture, for early phase shape planning, using the styles of renowned architects. The study employed the following approaches: 1) Intensive image generation based on the styles of 20 architects to test the AI's recognition ability and image quality. 2) Additional training was conducted for architects with low recognition rates to construct an enhanced learning model in the quality of image generation. 3) In addition to generating architectural visualization images using existing architects' design styles, alternative styles were proposed through design combinations, aiming to concretize ambiguous idea communication in the early stages of design and enhance its efficiency. The study sheds light on the future prospects of applying this generative AI model in the field of architecture | |
dc.language | English | |
dc.relation.ispartofseries | Proceedings e report | |
dc.subject.classification | thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence | |
dc.subject.other | Design Style of Architects | |
dc.subject.other | Generative AI | |
dc.subject.other | Image Generation | |
dc.subject.other | Fine-tuning | |
dc.title | Chapter Generative Design Intuition from the Fine-Tuned Models of Named Architects’ Style | |
dc.type | chapter | |
oapen.identifier.doi | 10.36253/979-12-215-0289-3.91 | |
oapen.relation.isPublishedBy | bf65d21a-78e5-4ba2-983a-dbfa90962870 | |
oapen.relation.isbn | 9791221502893 | |
oapen.series.number | 137 | |
oapen.pages | 9 | |
oapen.place.publication | Florence |