Surface Defect-Extended BIM Generation Leveraging UAV Images and Deep Learning.

ABSTRACT: Defect inspection of existing buildings is receiving increasing attention for digitalization transfer in the construction industry. The development of drone technology and artificial intelligence has provided powerful tools for defect inspection of buildings. However, integrating defect inspection information detected from UAV images into semantically rich building information modeling (BIM) is still challenging work due to the low defect detection accuracy and the coordinate difference between UAV images and BIM models. In this paper, a deep learning-based method coupled with transfer learning is used to detect defects accurately; and a texture mapping-based defect parameter extraction method is proposed to achieve the mapping from the image U-V coordinate system to the BIM project coordi

SUBMITTER: Yang L 

PROVIDER: S-EPMC11243814 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature