Deep learning models for analysis of non‐destructive evaluation data to evaluate reinforced concrete bridge decks: A survey
Abstract Application of deep learning (DL) for automatic condition assessment of bridge decks has been on the raise in the last few years. From the published literature, it is evident that lot of research efforts has been done in identifying the surface defects such as cracks, potholes, spalling and...
Saved in:
Main Authors: | Dayakar Naik Lavadiya, Sattar Dorafshan |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2025-01-01
|
Series: | Engineering Reports |
Subjects: | |
Online Access: | https://doi.org/10.1002/eng2.12608 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Degree of corrosion and other deterioration effects in highway bridge deck component using non-destructive self potential and vibration testing: case study from SW Nigeria
by: O. O. Falowo, et al.
Published: (2025-01-01) -
Bending performance and design of reinforced concrete ribbed bridge deck slabs retrofitted with steel-plate reinforcement
by: Jianshuai Liu, et al.
Published: (2025-01-01) -
Experimental and Numerical Investigation of Welding Residual Stress of U-Rib Joints in Orthotropic Steel Bridge Decks
by: Zhiqiang Huang, et al.
Published: (2025-01-01) -
Frequency multiplexed photothermal correlation tomography for non-destructive evaluation of manufactured materials
by: Pengfei Zhu, et al.
Published: (2025-01-01) -
Mechanical analysis and experimental study on the shear performance of waterproof adhesive layer toward concrete bridge deck pavement
by: Xiaoqiu Lei, et al.
Published: (2025-07-01)