Automated Pavement Crack Segmentation Using U-Net-Based Convolutional Neural Network

Automated Pavement Crack Segmentation Using U-Net-Based Convolutional Neural Network

Automated pavement crack image segmentation is challenging because of inherent irregular patterns, lighting conditions, and noise in images. Conventional approaches require a substantial amount of feature engineering to differentiate crack regions from non-affected regions. In this paper, we propose...

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Bibliographic Details
Main Authors: Stephen L. H. Lau, Edwin K. P. Chong, Xu Yang, Xin Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Convolutional neural network
deep learning
fully convolutional network
pavement crack segmentation
U-Net
Online Access:https://ieeexplore.ieee.org/document/9121269/

Internet

https://ieeexplore.ieee.org/document/9121269/

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