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Chapter Generative Design Intuition from the Fine-Tuned Models of Named Architects’ Style
Jeong, Hyun, Yoo, Youngjin, Kim, Youngchae, Cha, SeungHyun, Lee, Jin-Kook

Chapter Generative Design Intuition from the Fine-Tuned Models of Named Architects’ Style

Humanities & Social Sciences Open Access Books Published 2024 Verification Pending

Overview & Synopsis

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

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Document Information

Document Title Chapter Generative Design Intuition from the Fine-Tuned Models of Named Architects’ Style
Author / Organization Jeong, Hyun, Yoo, Youngjin, Kim, Youngchae, Cha, SeungHyun, Lee, Jin-Kook
Subject & Discipline Design Style of Architects
Categories Humanities & Social Sciences Open Access Books
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website OAPEN Library (www.oapen.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-80986
Original Source Link Visit Source Page on www.oapen.org »