Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network

H Chu, P Chun - Computer‐Aided Civil and Infrastructure …, 2024‏ - Wiley Online Library
High‐resolution (HR) crack images offer more detailed information for assessing structural
conditions compared to low‐resolution (LR) images. This wealth of detail proves …

Hybrid deep learning architecture for rail surface segmentation and surface defect detection

Y Wu, Y Qin, Y Qian, F Guo, Z Wang… - Computer‐Aided Civil …, 2022‏ - Wiley Online Library
Rail surface defects (RSDs) are a major problem that reduces operation safety.
Unfortunately, the existing RSD detection systems have very limited accuracy. Current …

Intelligent recognition of defects in high‐speed railway slab track with limited dataset

X Cai, X Tang, S Pan, Y Wang, H Yan… - … ‐Aided Civil and …, 2024‏ - Wiley Online Library
During the regular service life of high‐speed railway (HSR), there might be serious defects
in the concrete slabs of the infrastructure systems, which may further significantly affect …

Multiclass seismic damage detection of buildings using quantum convolutional neural network

S Bhatta, J Dang - Computer‐Aided Civil and Infrastructure …, 2024‏ - Wiley Online Library
The traditional visual inspection technique for damage assessment of buildings immediately
after an earthquake can be time‐consuming, labor‐intensive, and risky. Numerous studies …

Dynamics‐based cross‐domain structural damage detection through deep transfer learning

Y Lin, Z Nie, H Ma - Computer‐Aided Civil and Infrastructure …, 2022‏ - Wiley Online Library
Structural damage detection (SDD) still suffers from environmental uncertainties or modeling
errors, causing a gap between the numerical model and the real structure. It results in …

Self‐training approach for crack detection using synthesized crack images based on conditional generative adversarial network

S Shim - Computer‐Aided Civil and Infrastructure Engineering, 2024‏ - Wiley Online Library
Urban infrastructure plays a crucial role in determining the quality of life for citizens.
However, given the increasing number of aging infrastructures, regular inspections are …

Semi‐supervised learning based on convolutional neural network and uncertainty filter for façade defects classification

J Guo, Q Wang, Y Li - Computer‐Aided Civil and Infrastructure …, 2021‏ - Wiley Online Library
Develo** a classifier to identify the defects from façade images using deep learning
requires abundant labeled images. However, it is time‐consuming and uneconomical to …

Deep learning‐based automatic classification of three‐level surface information in bridge inspection

H Zhang, Z Shen, Z Lin, L Quan… - Computer‐Aided Civil …, 2024‏ - Wiley Online Library
Bridge inspection ensures that in‐service bridges are managed and maintained in
conformity. To enhance the accuracy and efficiency of bridge inspection, an automatic …

Neural operator for structural simulation and bridge health monitoring

C Kaewnuratchadasorn, J Wang… - Computer‐Aided Civil …, 2024‏ - Wiley Online Library
Infusing deep learning with structural engineering has received widespread attention for
both forward problems (structural simulation) and inverse problems (structural health …

A self‐supervised monocular depth estimation model with scale recovery and transfer learning for construction scene analysis

J Shen, W Yan, S Qin, X Zheng - Computer‐Aided Civil and …, 2023‏ - Wiley Online Library
Estimating the depth of a construction scene from a single red‐green‐blue image is a crucial
prerequisite for various applications, including work zone safety, localization, productivity …