Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network

Zhong Zhou; Junjie Zhang; Chenjie Gong

doi:10.1111/mice.13003

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JOURNAL ARTICLE

Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network

Zhong Zhou Junjie Zhang Chenjie Gong

Year: 2023 Journal: Computer-Aided Civil and Infrastructure Engineering Vol: 38 (17)Pages: 2491-2510 Publisher: Wiley

DOI: 10.1111/mice.13003

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Keywords:

Computer science Convolutional neural network Segmentation Artificial intelligence Transformer Pattern recognition (psychology) Computer vision Engineering Voltage

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141

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28.84

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1.00

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Topics

Infrastructure Maintenance and Monitoring

Physical Sciences → Engineering → Civil and Structural Engineering

Geotechnical Engineering and Underground Structures

Physical Sciences → Engineering → Civil and Structural Engineering

Tunneling and Rock Mechanics

Physical Sciences → Engineering → Civil and Structural Engineering

Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network

Metrics

Citation History

Topics

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