Deep learning based water leakage detection for shield tunnel lining

Author:

Liu Shichang,Xu Xu,Jeon Gwanggil,Chen Junxin,He Ben-Guo

Publisher

Springer Science and Business Media LLC

Reference46 articles.

1. Li C, Wang M, Gao X, Yang B. Research on on-site monitoring and measurement technology of tunnel. IOP Conference Series: Earth and Environmental Science, 2020, 455(1): 012154

2. Ma D, Fang H, Wang N, Zhang C, Dong J, Hu H. Automatic detection and counting system for pavement cracks based on PCGAN and YOLO-MF. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(11): 22166–22178

3. Zhou Q, Qu Z, Li Y X, Ju F R. Tunnel crack detection with linear seam based on mixed attention and multiscale feature fusion. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1–11

4. Meng S, Kuang S, Ma Z, Wu Y. MtlrNet: An effective deep multitask learning architecture for rail crack detection. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1–10

5. Ali R, Chuah J H, Talip M S A, Mokhtar N, Shoaib M A. Structural crack detection using deep convolutional neural networks. Automation in Construction, 2022, 133: 103989

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