Detail publikace

Traffic Analysis Using Machine Learning Approach

ZELENÝ, O. FRÝZA, T.

Originální název

Traffic Analysis Using Machine Learning Approach

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální 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

Autoři

ZELENÝ, O.; FRÝZA, T.

Vydáno

26. 4. 2022

Nakladatel

Brno University of Technology, Faculty of ERlectronic Engineering and Communication

Místo

Brno

ISBN

978-80-214-6029-4

Kniha

PROCEEDINGS I OF THE 28TH STUDENT EEICT 2022 General papers

Edice

1

Strany od

265

Strany do

268

Strany počet

4

URL

https://www.eeict.cz/eeict_download/archiv/sborniky/EEICT_2022_sbornik_1_v2.pdf

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"
}