Acknowledgement
본 연구는 한국과학재단이 주관하는 대학 중점연구소지원사업(No. NRF-2018R1A6A1A07025819)과 신진연구지원사업(No. NRF-2020R1C1C1005406)의 지원을 받아 수행되었습니다.
With the development of digital technology, construction companies at home and abroad are in the process of computerizing work and site information for the purpose of improving work efficiency. To this end, various technologies such as BIM, digital twin, and AI-based safety management have been developed, but the accuracy and completeness of the related technologies are insufficient to be applied to the field. In this paper, the learning data that has undergone a pre-processing process optimized for recognition of construction information based on structural members is trained on an existing artificial intelligence model to improve recognition accuracy and evaluate its effectiveness. The artificial intelligence model optimized for the structural member created through this study will be used as a base technology for the technology that needs to confirm the safety of the structure in the future.
본 연구는 한국과학재단이 주관하는 대학 중점연구소지원사업(No. NRF-2018R1A6A1A07025819)과 신진연구지원사업(No. NRF-2020R1C1C1005406)의 지원을 받아 수행되었습니다.