Show source-provided references
1. Design and development of highway tunnel maintenance and management system
2. BIM, machine learning and computer vision techniques in underground construction: Current status and future perspectives
10.1016/j.tust.2020.103677 ↗4. Development of an inspection system for cracks in a concrete tunnel lining
10.1139/l07-008 ↗6. Gavilán, M., Sánchez, F., Ramos, J.A., and Marcos, O. (2013, January 9–11). Mobile inspection system for high-resolution assessment of tunnels. Proceedings of the 6th International Conference on Structural Health Monitoring of Intelligent Infrastructure, Hongkong, China.
8. Yasuda, T., Yamamoto, H., Enomoto, M., and Nitta, Y. (2020, January 27–28). Smart tunnel inspection and assessment using mobile inspection vehicle, non-contact radar and ai BT. Proceedings of the 37th International Symposium on Automation and Robotics in Construction: From Demonstration to Practical Use—To New Stage of Construction Robot, ISARC 2020, Kitakyushu, Japan.
10.22260/ISARC2020/0190 ↗9. Damage Assessment of Tunnel Lining by Mobile Laser Scanning: Pittsburgh, Pennsylvania, Implementation Phase of FHWA SHRP 2 R06G Project
10.3141/2642-18 ↗10. Idoux, M. Multisensor system for tunnel inspection. Infrared Components and Their Applications, SPIE.
11. Model test study of factors affecting automatic detection performance of cracks in tunnel lining
12. Design of Vertically-Aligned Binocular Omnistereo Vision Sensor with Face-to-Back Configuration
13. Review and Developing Trend of Railway Tunnel Detection Technology
14. Review of Rapid Test Vehicles for Highway Tunnel Structure
15. Optimal modeling and parameter identification for visual system of the road tunnel detection vehicle
16. Liu, X. (2018). Design and Implementation of Road Tunnel Intelligent Detection System. Mach. Des. Manuf., Available online: https://www.cnki.com.cn/Article/CJFDTotal-JSYZ201808020.htm.
19. Bendris, B., and Becerra, J.C. (2022). Design and Experimental Evaluation of an Aerial Solution for Visual Inspection of Tunnel-like Infrastructures. Remote Sens., 14.
10.3390/rs14010195 ↗20. Shigeta, Y., Maeda, K., Yamamoto, H., Yasuda, T., Kaise, S., Maegawa, K., and Ito, T. (2019). Tunnel deformation evaluation by mobile mapping system. Tunnels and Underground Cities: Engineering and Innovation Meet Archaeology, Architecture and Art, CRC Press.
10.1201/9780429424441-328 ↗21. Cai, J.L., Xie, X.Y., Zhou, B., Zhou, Y.X., and Zeng, W.C. (2020). Rapid automatic inspection system for tunnel lining based on a mobile vehicle. Tunnels and Underground Cities: Engineering and Innovation Meet Archaeology, Architecture and Art: Volume 5: Innovation in Underground Engineering, Materials and Equipment—Part 1, CRC Press.
10.1201/9780429424441-195 ↗22. Multiscale and adversarial learning-based semi-supervised semantic segmentation approach for crack detection in concrete structures
10.1109/ACCESS.2020.3022786 ↗23. Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks
10.1111/mice.12263 ↗