[HTML][HTML] Self-training method for structural crack detection using image blending-based domain mixing and mutual learning
Deep learning-based structural crack detection utilizing fully supervised methods requires
laborious labeling of training data. Moreover, models trained on one dataset often …
laborious labeling of training data. Moreover, models trained on one dataset often …
A semi‐supervised approach for building wall layout segmentation based on transformers and limited data
In structural design, accurately extracting information from floor plan drawings of buildings is
essential for building 3D models and facilitating design automation. However, deep learning …
essential for building 3D models and facilitating design automation. However, deep learning …
Robust ELM-PID tracing control on autonomous mobile robot via transformer-based pavement crack segmentation
Pavement crack tracing is paramount to missions encompassing automated crack sealing
for road maintenance. However, existing methods still face several challenges, including the …
for road maintenance. However, existing methods still face several challenges, including the …
Enhanced pavement crack segmentation with minimal labeled data: a triplet attention teacher-student framework
MA Mohammed, Z Han, Y Li, Z Al-Huda… - International Journal of …, 2024 - Taylor & Francis
Effective crack detection is critical for pavement maintenance, yet existing methods face
significant challenges. Deep learning has become a popular solution due to its superior …
significant challenges. Deep learning has become a popular solution due to its superior …
A fatigue crack prediction method based on inductive semi-supervised learning and Lamb-wave monitoring for orthotropic steel bridge deck
L Shi, B Cheng, S Xiang - Engineering Structures, 2025 - Elsevier
Orthotropic steel bridge deck suffers from fatigue cracking due to its orthotropic configuration
and cyclic vehicular load. Hence, fatigue crack monitoring and prediction are crucial for …
and cyclic vehicular load. Hence, fatigue crack monitoring and prediction are crucial for …
Robust feature knowledge distillation for enhanced performance of lightweight crack segmentation models
Vision-based crack detection faces deployment challenges due to the size of robust models
and edge device limitations. These can be addressed with lightweight models trained with …
and edge device limitations. These can be addressed with lightweight models trained with …
ANP-Net: attention neural processes network for semi-supervised pavement defect semantic segmentation
R Pang, J Ning, X Leng, C Chen… - International Journal of …, 2024 - Taylor & Francis
The extensive and rapid development of road transportation systems across diverse
geographical landscapes underscores the imperative for efficient maintenance strategies …
geographical landscapes underscores the imperative for efficient maintenance strategies …
Deep Learning Applications for Analysing Concrete Surface Cracks
Deep learning is transforming concrete crack analysis into civil engineering, enabling
automated, accurate, and scalable detection essential for maintaining infrastructure like …
automated, accurate, and scalable detection essential for maintaining infrastructure like …
Limited Label-Support Pavement Damage Segmentation Network with Uniform Rectification and Intrinsic Cross-Dimensional Constraint
Most recent research on pavement damage segmentation focuses on fully supervised
learning to achieve solid performance. The major limitation of this strategy in practice is the …
learning to achieve solid performance. The major limitation of this strategy in practice is the …