Conference paper

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.
Publication language:english
Original title:Detection of Traffic Violations of Road Users Based on Convolutional Neural Networks
Title (cs):Detekce dopravních přestupků uživatelů pozemních komunikací s pomocí neuronových sítí
Pages:1-6
Proceedings:2018 14th Symposium on Neural Networks and Applications (NEUREL)
Conference:2018 14th Symposium on Neural Networks and Applications (NEUREL)
Place:Belgrade, RS
Year:2018
ISBN:978-1-5386-6974-7
DOI:10.1109/NEUREL.2018.8586996
Publisher:IEEE Signal Processing Society
Keywords
camera calibration, convolutional neural networks, pedestrian detection, traffic violation, vehicle detection
Annotation
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.  
BibTeX:
@INPROCEEDINGS{
   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 = {http://www.fit.vutbr.cz/research/view_pub.php?id=11850}
}

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