Detail výsledku

Traffic Analysis Using Machine Learning Approach

ZELENÝ, O.; FRÝZA, T. Traffic Analysis Using Machine Learning Approach. In PROCEEDINGS I OF THE 28TH STUDENT EEICT 2022 General papers. 1. Brno: Brno University of Technology, Faculty of ERlectronic Engineering and Communication, 2022. p. 265-268. ISBN: 978-80-214-6029-4.
Typ
článek ve sborníku konference
Jazyk
anglicky
Autoři
Zelený Ondřej, Ing., FEKT (FEKT)
Frýza Tomáš, doc. Ing., Ph.D., UREL (FEKT)
Abstrakt

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.

Klíčová slova

Deep learning, Computer vision, Traffic analysis, Convolutional Neural
Networks, You Only Look Once, COCO dataset

URL
Rok
2022
Strany
265–268
Sborník
PROCEEDINGS I OF THE 28TH STUDENT EEICT 2022 General papers
Řada
1
Konference
STUDENT EEICT 2022
ISBN
978-80-214-6029-4
Vydavatel
Brno University of Technology, Faculty of ERlectronic Engineering and Communication
Místo
Brno
EID Scopus
2-s2.0-85162016983
BibTeX 
@inproceedings{BUT186978,
  author="Ondřej {Zelený} and Tomáš {Frýza}",
  title="Traffic Analysis Using Machine Learning Approach",
  booktitle="PROCEEDINGS I OF THE 28TH STUDENT EEICT 2022 General papers",
  year="2022",
  series="1",
  pages="265--268",
  publisher="Brno University of Technology, Faculty of ERlectronic Engineering and Communication",
  address="Brno",
  isbn="978-80-214-6029-4",
  url="https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf"
}
Pracoviště
Ústav radioelektroniky (UREL)
Nahoru