A deep learning framework based on improved self‐supervised learning for ground‐penetrating radar tunnel lining inspection
| Author(s): |
Jian Huang
(School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China)
Xi Yang (School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China) Feng Zhou (School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China) Xiaofeng Li (School of Mechanical Engineering and Electronic Information China University of Geosciences (Wuhan) Wuhan China) Bin Zhou (China Railway Southwest Research Institute Co. LTD Chengdu China) Song Lu (China Railway Southwest Research Institute Co. LTD Chengdu China) Sergey Ivashov (Remote Sensing Laboratory Bauman Moscow State Technical University Moscow Russia) Iraklis Giannakis (School of Geosciences University of Aberdeen Aberdeen UK) Fannian Kong (Norwegian Geotechnical Institute Oslo Norway) Evert Slob (Department of Geoscience and Engineering Delft University of Technology Delft The Netherlands) |
|---|---|
| Medium: | journal article |
| Language(s): | English |
| Published in: | Computer-Aided Civil and Infrastructure Engineering, October 2023, n. 6, v. 39 |
| DOI: | 10.1111/mice.13042 |
- About this
data sheet - Reference-ID
10725624 - Published on:
30/05/2023 - Last updated on:
15/03/2024
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