Intelligent detection of fastener defects in ballastless tracks based on deep learning
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- Authors
- Ye, W., Ren, J., Lu, C., Zhang, A. A., Zhan, Y., & Liu, J.
- Affiliations
- Southwest Jiaotong University (CN)
- Corresponding author
- Ren, Juanjuan
- Venue
- Automation in Construction
- Publisher
- Elsevier BV
- Published
- 2024-03
- Volume
- 159
- Pages
- 105280
- ISSN
- 0926-5805 (ISSN-L)
- OpenAlex
- W4391001533
- Cited by
- 42
- References
- 52
- Citations by year
- 2026: 16 · 2025: 17 · 2024: 9
- FWCI
- 7.01
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Automation in Construction (publishedVersion)
- Funders
- National Natural Science Foundation of China (52278461, 52022085, 52308467)
- Sichuan Province Youth Science and Technology Innovation Team (2022JDTD0015)
- National Key Research and Development Program of China (2021YFF0502100)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Keywords
- ballastless track, object detection, heatmaps, 3D laser scanning, high-speed rail, inference speed
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