Geometrical flow‐guided fast beamlet transform for crack detection

Author:

Lin Zhe12ORCID,Zhao Xiaohua1

Affiliation:

1. Department of Civil and Environmental EngineeringShantou UniversityShantou515063People's Republic of China

2. Department of ComputerShantou PolytechnicShantou515078People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Quantitative Evaluation to Detect Crack Depth in Beams Based on CNN-RNN-LSTM Approach;2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS);2023-10-18

2. Automated Bridge Crack Detection Based on Improving Encoder–Decoder Network and Strip Pooling;Journal of Infrastructure Systems;2023-06

3. Grouping Beamlet Transform for Surface Crack Detection;2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE);2023-01-06

4. Computer vision framework for crack detection of civil infrastructure—A review;Engineering Applications of Artificial Intelligence;2023-01

5. PDNet: Improved YOLOv5 Nondeformable Disease Detection Network for Asphalt Pavement;Computational Intelligence and Neuroscience;2022-07-07

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