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Fine‐grained crack segmentation for high‐resolution images via a multiscale cascaded network
High‐resolution (HR) crack images offer more detailed information for assessing structural
conditions compared to low‐resolution (LR) images. This wealth of detail proves …
conditions compared to low‐resolution (LR) images. This wealth of detail proves …
Hybrid deep learning architecture for rail surface segmentation and surface defect detection
Rail surface defects (RSDs) are a major problem that reduces operation safety.
Unfortunately, the existing RSD detection systems have very limited accuracy. Current …
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 …
in the concrete slabs of the infrastructure systems, which may further significantly affect …
Multiclass seismic damage detection of buildings using quantum convolutional neural network
The traditional visual inspection technique for damage assessment of buildings immediately
after an earthquake can be time‐consuming, labor‐intensive, and risky. Numerous studies …
after an earthquake can be time‐consuming, labor‐intensive, and risky. Numerous studies …
Dynamics‐based cross‐domain structural damage detection through deep transfer learning
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 …
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 …
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
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 …
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 …
conformity. To enhance the accuracy and efficiency of bridge inspection, an automatic …
Neural operator for structural simulation and bridge health monitoring
Infusing deep learning with structural engineering has received widespread attention for
both forward problems (structural simulation) and inverse problems (structural health …
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 …
prerequisite for various applications, including work zone safety, localization, productivity …