Autonomous concrete crack detection using deep fully convolutional neural network

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A cluster-based data splitting method for small sample and class imbalance problems in impact damage classification

Doan, Q. H., Mai, S. H., Do, Q. T., & Thai, D. (2022) · Applied Soft Computing · doi:10.1016/j.asoc.2022.108628 · Cited by 36

Image-based intelligent detection of typical defects of complex subway tunnel surface

Xu, L., Wang, Y., Dong, A., Zhu, L., Shi, H., & Yu, Z. (2023) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2023.105266 · Cited by 36

Automated pixel-level crack monitoring system for large-scale underground infrastructure – A case study at CERN

Ouyang, A., Murro, V. D., Cull, M., Cunningham, R., Osborne, J. A., & Li, Z. (2023) · Tunnelling and Underground Space Technology · doi:10.1016/j.tust.2023.105310 · Cited by 36

A survey on crack detection in concrete surface using image processing and machine learning

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Vision-Based Autonomous Crack Detection of Concrete Structures Using a Fully Convolutional Encoder–Decoder Network

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Autonomous Concrete Crack Semantic Segmentation Using Deep Fully Convolutional Encoder–Decoder Network in Concrete Structures Inspection

Pu, R., Ren, G., Li, H., Jiang, W., Zhang, J., & Qin, H. (2022) · Buildings · doi:10.3390/buildings12112019 · Cited by 24

Crack Detection in Buildings Using Convolutional Neural NetworkPreprint

Soni, A. N. (2019) · SSRN Electronic Journal · Cited by 13

Image-based concrete crack detection in tunnels using deep fully convolutional networks

Ren, Y., Huang, J., Hong, Z., Lu, W., Yin, J., Zou, L., & Shen, X. (2019) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2019.117367 · Cited by 522

Research on automatic detection and analysis of concrete cracks based on deep convolutional neural network architecture

Li, J., Wang, B., An, P., Zhao, J., & Luo, Y. (2025) · Advances in Structural Engineering · doi:10.1177/13694332251375209 · Cited by 3