Detail publikačního výsledku

Classification of Traffic Signs by Convolutional Neural Networks

MÍVALT, F.; NEJEDLÝ, P.

Originální název

Classification of Traffic Signs by Convolutional Neural Networks

Anglický název

Classification of Traffic Signs by Convolutional Neural Networks

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

The paper presented here describes traffic signs classification method based on a convolutional neural network (CNN). The CNN was trained and tested on the public database of German traffic signs with 43 mostly used traffic sign types. Proposed technique achieved overall classification F1 score 89.97 percent on a hidden testing dataset.

Anglický abstrakt

The paper presented here describes traffic signs classification method based on a convolutional neural network (CNN). The CNN was trained and tested on the public database of German traffic signs with 43 mostly used traffic sign types. Proposed technique achieved overall classification F1 score 89.97 percent on a hidden testing dataset.

Klíčová slova

Machine learning; Convolutional neural networks; Traffic signs recognition

Klíčová slova v angličtině

Machine learning; Convolutional neural networks; Traffic signs recognition

Autoři

MÍVALT, F.; NEJEDLÝ, P.

Rok RIV

2019

Vydáno

26.04.2018

Nakladatel

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních

Místo

Brno

ISBN

978-80-214-5614-3

Kniha

Proceedings of the 24th Conference STUDENT EEICT 2018

Strany od

188

Strany do

190

Strany počet

3

URL

http://www.feec.vutbr.cz/EEICT/archiv/sborniky/EEICT_2018_sbornik.pdf

BibTex

@inproceedings{BUT147412,
  author="Filip {Mívalt} and Petr {Nejedlý}",
  title="Classification of Traffic Signs by Convolutional Neural Networks",
  booktitle="Proceedings of the 24th Conference STUDENT EEICT 2018",
  year="2018",
  number="první",
  pages="188--190",
  publisher="Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních",
  address="Brno",
  isbn="978-80-214-5614-3",
  url="http://www.feec.vutbr.cz/EEICT/archiv/sborniky/EEICT_2018_sbornik.pdf"
}