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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/8793450http://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] > COMPUTER SCIENCE(소프트웨어학부) > Articles
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