YOLOv5-Pothole: An Improved Pothole Perception Method Based on YOLOv5-Seg-Reference-Cited by-同舟云学术

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YOLOv5-Pothole: An Improved Pothole Perception Method Based on YOLOv5-Seg

Published:2023-12-08 Issue: Volume: Page:
ISSN:
Container-title:2023 2nd International Conference on Artificial Intelligence, Human-Computer Interaction and Robotics (AIHCIR)
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Author:

Chen Xiaokang¹,Ma Nan²,Wang Mohan³

Affiliation:

1. Beijing Union University,Beijing Key Laboratory of Information Service Engineering,Beijing,China

2. Beijing University of Technology,Engineering Research Center of Intelligence Perception and Autonomous Control,Beijing,China

3. Beijing University of Technology,Faculty of Information and Technology,Beijing,China

Funder

Beijing Natural Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10505329/10505330/10505438.pdf?arnumber=10505438

Reference20 articles.

1. Review of Recent Automated Pothole-Detection Methods

2. Pothole Detection Based on Disparity Transformation and Road Surface Modeling

3. Road Damage Detection Based on Unsupervised Disparity Map Segmentation

4. Pavement Pothole Detection Based on 3D Laser Point Cloud

5. Real-Time Road Pothole Mapping Based on Vibration Analysis in Smart City

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 deep learning model to assist visually impaired in pothole detection using computer vision;Decision Analytics Journal;2024-09

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