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Title	Research On Improved Yolov7 Based Vehicle Speed And Traffic Flow Detection System
ID_Doc	45420
Authors	Ping A.; Xue Y.; Yao B.; Xiao S.; Zhang X.; Li L.
Year	2023
Published	Frontiers in Artificial Intelligence and Applications, 373
DOI	http://dx.doi.org/10.3233/FAIA230852
Abstract	The detection of speed and traffic flow is one of the important issues in the current smart city construction and intelligent transportation development process. The automatic detection of speed and traffic flow through video information in road traffic is conducive to optimising road traffic and transport management, strengthening urban management and improving the efficiency of urban transport and services. Therefore, the study of vehicle speed and traffic flow detection systems is of great practical value. To address the issue of urban road transport management, an improved YOLOv7-based vehicle speed and traffic flow detection system was designed and implemented based on traffic video data, and the system was validated and analysed based on the video data. © 2023 The Authors.
Author Keywords	Attentional mechanisms; Speed detection; Target tracking; Traffic flow detection; YOLOv7

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