Application of Traffic Cone Target Detection Algorithm Based on Improved YOLOv5

Application of Traffic Cone Target Detection Algorithm Based on Improved YOLOv5

To improve the automation level of highway maintenance operations, the lightweight YOLOv5-Lite-s neural network was deployed in embedded devices to assist an automatic traffic cone retractor in completing recognition and positioning operations. The system used the lightweight shuffle Net network as...

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Bibliographic Details
Main Authors: Mingwu Wang, Dan Qu, Zedong Wu, Ao Li, Nan Wang, Xinming Zhang
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Sensors
Subjects:
road maintenance
target detection
network deployment
deep learning
automatic traffic cone retractor
Online Access:https://www.mdpi.com/1424-8220/24/22/7190
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