이진국 교수
Jinkook Lee
연세대학교 실내건축학과 · 공학
연구실 소개
이 교수의 연구실은 건축·건설 분야의 디지털 전환을 선도하는 연구를 수행하고 있습니다. 주요 연구 방향은 BIM 기반 자동 허가 시스템, 자연어 처리를 활용한 건축 규칙 번역, 생성형 AI를 활용한 초기 설계 시각화, 그리고 증강 및 몰입형 가상현실 기반 디자인 의사결정 지원 기술 개발입니다. 특히, 딥러닝과 자연어 처리 기반의 스마트 설계 지원 시스템 개발에 초점을 맞추고 있습니다.
연구 현황
연구 성과 추이
표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.
주요 논문
15Abstract The Building Information Modeling (BIM) and its applications enable an automatic building permit process based on 3D building models and their associated information. A crucial part of the building permit process is the interpretation and transformation of natural language-based building regulation into a computer-readable and executable format. As other countries and their projects have developed a certain type of rule-translation methods, KBimCode, part of the KBim application series,
Abstract This paper elucidates an approach that utilizes generative artificial intelligence (AI) to develop alternative architectural design options based on local identity. The advancement of AI technologies has increasingly piqued the interest of the architecture, engineering, construction, and facility management industry. Notably, the topic of “visualization” has gained prominence as a means for enhancing communication related to a project, especially in the early phases of design. This stud
Abstract This paper discusses an approach to augmented virtual reality (AVR) and 360-degree spatial visualization. The approach involves locating stereoscopic three-dimensional virtual objects into a real off-site panorama, supporting spatial remodel design decision-making through realistic comparisons. Previous studies have shown that in the design process, end-user engagement promotes the quality and satisfaction of design solutions. Immersive media such as virtual reality (VR) and augmented r
This paper describes an approach for identifying and appending interior design style information stochastically with reference images and a deep-learning model. In the field of interior design, design style is a useful concept and has played an important role in helping people understand and communicate interior design. Previous studies have focused on how the interior design style categories can be defined. On the other hand, this paper focuses on how stochastically recognizing the design style
Abstract This paper describes an approach to extracting a predicate-argument structure (PAS) in building design rule sentences using natural language processing (NLP) and deep learning models. For the computer to reason about the compliance of building design, design rules represented by natural language must be converted into a computer-readable format. The rule interpretation and translation processes are challenging tasks because of the vagueness and ambiguity of natural language. Many studie
Abstract This study introduces a novel approach to architectural visualization using generative artificial intelligence (AI), particularly emphasizing text-to-image technology, to remarkably improve the visualization process right from the initial design phase within the architecture, engineering, and construction industry. By creating more than 10 000 images incorporating an architect’s personal style and characteristics into a residential house model, the effectiveness of base AI models. Furth
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