Crack Detection Method on Surface of Tunnel Lining
- Title
- Crack Detection Method on Surface of Tunnel Lining
- Author
- 문영식
- Keywords
- Concrete Inspection; Convolutional Neural Network; Crack Detection; Tunnel Inspection
- Issue Date
- 2019-06
- Publisher
- IEEE
- Citation
- 2019 34th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC), Article no. 8793450
- Abstract
- Crack detection on surface of tunnel lining is one of the most important tasks in concrete structure inspection field. Naked eye inspection method is widely used in general but it needs huge resources. To solve the issue, many methods have been proposed based on convolutional neural network but they show disconnected crack results with thin or blurred crack image. To overcome this problem, we propose a multiscale feature fusion method for crack detection. Experientially, results show that performance of our method was improved over the previous methods.
- URI
- https://ieeexplore.ieee.org/abstract/document/8793450https://repository.hanyang.ac.kr/handle/20.500.11754/121873
- ISBN
- 978-1-7281-3271-6
- DOI
- 10.1109/ITC-CSCC.2019.8793450
- Appears in Collections:
- COLLEGE OF COMPUTING[E](소프트웨어융합대학) > COMPUTER SCIENCE(소프트웨어학부) > Articles
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