Traffic Analysis Using Machine Learning Approach.

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Zelený, O.
Frýza, T.

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Mark

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Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

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Abstract

This paper provides insight to the YOLOv5 deep learning architecture and its use for vehicle detection and classification in order to improve traffic management in larger cities and busy roads. The paper presents simple system with one fixed camera and Jetson Nano, a computer for embedded and AI application, to detect and classify vehicles.

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Proceedings I of the 28st Conference STUDENT EEICT 2022: General papers. s. 265-268. ISBN 978-80-214-6029-4
https://conf.feec.vutbr.cz/eeict/index/pages/view/ke_stazeni

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Peer-reviewed

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en

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