Original title: Traffic Analysis Using Machine Learning Approach.
Authors: Zelený, O. ; Frýza, T.
Document type: Papers
Language: eng
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
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.
Keywords: COCO dataset; Computer vision; Convolutional Neural Networks; Deep learning; Traffic analysis; You Only Look Once
Host item entry: Proceedings I of the 28st Conference STUDENT EEICT 2022: General papers, ISBN 978-80-214-6029-4

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/209342

Permalink: http://www.nusl.cz/ntk/nusl-524769


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers