Computer vision framework for crack detection of civil infrastructure—A review
Civil infrastructure (eg, buildings, roads, underground tunnels) could lose its expected
physical and functional conditions after years of operation. Timely and accurate inspection …
physical and functional conditions after years of operation. Timely and accurate inspection …
Structural crack detection using deep convolutional neural networks
Abstract Convolutional Neural Networks (CNN) have immense potential to solve a broad
range of computer vision problems. It has achieved encouraging results in numerous …
range of computer vision problems. It has achieved encouraging results in numerous …
Efficient attention-based deep encoder and decoder for automatic crack segmentation
Recently, crack segmentation studies have been investigated using deep convolutional
neural networks. However, significant deficiencies remain in the preparation of ground truth …
neural networks. However, significant deficiencies remain in the preparation of ground truth …
[HTML][HTML] Automatic crack classification and segmentation on masonry surfaces using convolutional neural networks and transfer learning
Masonry structures represent the highest proportion of building stock worldwide. Currently,
the structural condition of such structures is predominantly manually inspected which is a …
the structural condition of such structures is predominantly manually inspected which is a …
Machine learning algorithms in civil structural health monitoring: A systematic review
M Flah, I Nunez, W Ben Chaabene… - Archives of computational …, 2021 - Springer
Abstract Applications of Machine Learning (ML) algorithms in Structural Health Monitoring
(SHM) have become of great interest in recent years owing to their superior ability to detect …
(SHM) have become of great interest in recent years owing to their superior ability to detect …
Vision transformer-based autonomous crack detection on asphalt and concrete surfaces
Previous research has shown the high accuracy of convolutional neural networks (CNNs) in
asphalt and concrete crack detection in controlled conditions. Yet, human-like generalisation …
asphalt and concrete crack detection in controlled conditions. Yet, human-like generalisation …
Hybrid semantic segmentation for tunnel lining cracks based on Swin Transformer and convolutional neural network
Z Zhou, J Zhang, C Gong - Computer‐Aided Civil and …, 2023 - Wiley Online Library
In the field of tunnel lining crack identification, the semantic segmentation algorithms based
on convolution neural network (CNN) are extensively used. Owing to the inherent locality of …
on convolution neural network (CNN) are extensively used. Owing to the inherent locality of …
Machine learning for crack detection: Review and model performance comparison
With the advancement of machine learning (ML) and deep learning (DL), there is a great
opportunity to enhance the development of automatic crack detection algorithms. In this …
opportunity to enhance the development of automatic crack detection algorithms. In this …
DMA-Net: DeepLab with multi-scale attention for pavement crack segmentation
Cracks are important indicators of pavement structural and operational conditions. Early
pavement crack detection and treatments can help extend pavement service life, reduce fuel …
pavement crack detection and treatments can help extend pavement service life, reduce fuel …
Image-based concrete crack detection in tunnels using deep fully convolutional networks
Y Ren, J Huang, Z Hong, W Lu, J Yin, L Zou… - … and Building Materials, 2020 - Elsevier
Automatic detection and segmentation of concrete cracks in tunnels remains a high-priority
task for civil engineers. Image-based crack segmentation is an effective method for crack …
task for civil engineers. Image-based crack segmentation is an effective method for crack …