A lightweight detection method of pavement potholes based on binocular stereo vision and deep learning-Reference-Cited by-同舟云学术

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A lightweight detection method of pavement potholes based on binocular stereo vision and deep learning

Published:2024-07 Issue: Volume:436 Page:136733
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Xing Chao,Zheng Guiping,Zhang Yongkang,Deng Hao,Li Mu,Zhang Lei,Tan Yiqiu

Publisher

Elsevier BV

Reference27 articles.

1. AAL-net: a lightweight detection method for road surface defects based on attention and data augmentation;Zhang;Appl. Sci.-Basel,2023

2. Automated pothole condition assessment in pavement using photogrammetry-assisted convolutional neural network;Ranyal;Int. J. Pavement Eng.,2023

3. Mechanism of physical hardening on the fracture characteristics of polymer-modified asphalt binder;Zhang;Constr. Build. Mater.,2023

4. Road surface defects detection based on IMU sensor;Zhang;IEEE Sens. J.,2022

5. Computer vision for road imaging and pothole detection: a state-of-the-art review of systems and algorithms;Ma;Transp. Saf. Environ.,2022

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Review of Vision-Based Pothole Detection Methods Using Computer Vision and Machine Learning;Sensors;2024-08-30

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