Tunnel Lining Crack Recognition Algorithm Integrating SK Attention and Cascade Neural Network
Tunnel Lining Crack Recognition Algorithm Integrating SK Attention and Cascade Neural Network
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Contents
Cracks are one of the main types of tunnel-lining defects. At present, there are no particularly good methods for identifying tunnel-lining cracks. The methods that are used are associated with problems such as poor robustness, low detection efficiency, and inconsistency in defect identification. Vision-based crack identification algorithms that us...
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Tunnel Lining Crack Recognition Algorithm Integrating SK Attention and Cascade Neural Network
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TN_cdi_proquest_journals_2848994807
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2848994807
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ISSN
2079-9292
E-ISSN
2079-9292
DOI
10.3390/electronics12153307
