@inproceedings{498de627036a4ea09dc23d01da3ea55c,
title = "Crack Detection Method on Surface of Tunnel Lining",
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.",
keywords = "Concrete Inspection, Convolutional Neural Network, Crack Detection, Tunnel Inspection",
author = "Han, \{Jeong Hoon\} and Cho, \{Yong Chae\} and Lee, \{Ho Gyeng\} and Yang, \{Hyeon Seok\} and Jeong, \{Woo Jin\} and Moon, \{Young Shik\}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 ; Conference date: 23-06-2019 Through 26-06-2019",
year = "2019",
month = jun,
doi = "10.1109/ITC-CSCC.2019.8793450",
language = "English",
series = "34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019",
}