Deep learning based image recognition for crack and leakage defects of metro shield tunnel
The performance of traditional visual inspection by handcrafted features for crack and
leakage defects of metro shield tunnel is hardly satisfactory nowadays because it is low …
leakage defects of metro shield tunnel is hardly satisfactory nowadays because it is low …
Real-time tunnel crack analysis system via deep learning
Cracks in the tunnel become an unavoidable problem in tunnel construction and tunnel
using. Cracks will affect the stability of the tunnel and have a negative impact on the …
using. Cracks will affect the stability of the tunnel and have a negative impact on the …
Automatic tunnel lining crack evaluation and measurement using deep learning
A tunnel is an imperative underground passageway that supports fast and uninterrupted
transportation. Over time, various factors, such as ageing, topographical changes, and …
transportation. Over time, various factors, such as ageing, topographical changes, and …
A fast detection method via region‐based fully convolutional neural networks for shield tunnel lining defects
Y Xue, Y Li - Computer‐Aided Civil and Infrastructure …, 2018 - Wiley Online Library
Tunnel lining defects are an important indicator reflecting the safety status of shield tunnels.
Inspired by the state‐of‐the‐art deep learning, a method for automatic intelligent …
Inspired by the state‐of‐the‐art deep learning, a method for automatic intelligent …
Automatic tunnel crack detection based on u-net and a convolutional neural network with alternately updated clique
G Li, B Ma, S He, X Ren, Q Liu - Sensors, 2020 - mdpi.com
Regular crack inspection of tunnels is essential to guarantee their safe operation. At present,
the manual detection method is time-consuming, subjective and even dangerous, while the …
the manual detection method is time-consuming, subjective and even dangerous, while the …
Automatic defect detection of metro tunnel surfaces using a vision-based inspection system
Due to the impact of the surrounding environment changes, train-induced vibration, and
human interference, damage to metro tunnel surfaces frequently occurs. Therefore …
human interference, damage to metro tunnel surfaces frequently occurs. Therefore …
Pixel-level tunnel crack segmentation using a weakly supervised annotation approach
Automatic crack detection plays an essential role in ensuring the safe operation of tunnels,
which is also challenging work in reality. In this paper, an innovative framework, which …
which is also challenging work in reality. In this paper, an innovative framework, which …
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 …
Automated crack classification for the CERN underground tunnel infrastructure using deep learning
D O'Brien, JA Osborne, E Perez-Duenas… - … and Underground Space …, 2023 - Elsevier
One early sign of tunnel structure deterioration originates in the form of cracking, and
therefore crack detection and resultant classification is integral for tunnel structural …
therefore crack detection and resultant classification is integral for tunnel structural …
[HTML][HTML] Deep learning based classification of rock structure of tunnel face
The automated interpretation of rock structure can improve the efficiency, accuracy, and
consistency of the geological risk assessment of tunnel face. Because of the high …
consistency of the geological risk assessment of tunnel face. Because of the high …