Faculty of Information Technology, BUT

Publication Details

Detection of Traffic Violations of Road Users Based on Convolutional Neural Networks

ŠPAŇHEL Jakub, SOCHOR Jakub and MAKAROV Aleksej. Detection of Traffic Violations of Road Users Based on Convolutional Neural Networks. In: 2018 14th Symposium on Neural Networks and Applications (NEUREL). Belgrade: IEEE Signal Processing Society, 2018, pp. 1-6. ISBN 978-1-5386-6974-7.
Czech title
Detekce dopravních přestupků uživatelů pozemních komunikací s pomocí neuronových sítí
Type
conference paper
Language
english
Authors
Špaňhel Jakub, Ing. (DCGM FIT BUT)
Sochor Jakub, Ing. (DCGM FIT BUT)
Makarov Aleksej (Vlatacom d.o.o.)
Keywords
camera calibration, convolutional neural networks, pedestrian detection, traffic violation, vehicle detection
Abstract
In this paper, we explore the implementation
of vehicle and pedestrian detection based on neural networks
in a real-world application. We suggest changes to the
previously published method with respect to capabilities of
low-powered devices, such as Nvidia Jetson platform. Our
experimental evaluation shows that detectors are capable of
running 10.7 FPS on Jetson TX2 and can be used in real-world applications.  
Published
2018
Pages
1-6
Proceedings
2018 14th Symposium on Neural Networks and Applications (NEUREL)
Conference
2018 14th Symposium on Neural Networks and Applications (NEUREL), SAVA Center Milentija Popovića 9 11070, Belgrade, Serbia, RS
ISBN
978-1-5386-6974-7
Publisher
IEEE Signal Processing Society
Place
Belgrade, RS
DOI
BibTeX
@INPROCEEDINGS{FITPUB11850,
   author = "Jakub \v{S}pa\v{n}hel and Jakub Sochor and Aleksej Makarov",
   title = "Detection of Traffic Violations of Road Users Based on Convolutional Neural Networks",
   pages = "1--6",
   booktitle = "2018 14th Symposium on Neural Networks and Applications (NEUREL)",
   year = 2018,
   location = "Belgrade, RS",
   publisher = "IEEE Signal Processing Society",
   ISBN = "978-1-5386-6974-7",
   doi = "10.1109/NEUREL.2018.8586996",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11850"
}
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