Detail publikačního výsledku

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

ŠPAŇHEL, J.; SOCHOR, J.; MAKAROV, A.

Original Title

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

English Title

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

Type

Paper in proceedings (conference paper)

Original 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.  

English 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.  

Keywords

camera calibration, convolutional neural networks, pedestrian detection, traffic violation, vehicle detection

Key words in English

camera calibration, convolutional neural networks, pedestrian detection, traffic violation, vehicle detection

Authors

ŠPAŇHEL, J.; SOCHOR, J.; MAKAROV, A.

RIV year

2019

Released

29.10.2018

Publisher

IEEE Signal Processing Society

Location

Belgrade

ISBN

978-1-5386-6974-7

Book

2018 14th Symposium on Neural Networks and Applications (NEUREL)

Pages from

1

Pages to

6

Pages count

6

Full text in the Digital Library

http://hdl.handle.net/

BibTex

@inproceedings{BUT155106,
  author="ŠPAŇHEL, J. and SOCHOR, J. and MAKAROV, A.",
  title="Detection of Traffic Violations of Road Users Based on Convolutional Neural Networks",
  booktitle="2018 14th Symposium on Neural Networks and Applications (NEUREL)",
  year="2018",
  pages="1--6",
  publisher="IEEE Signal Processing Society",
  address="Belgrade",
  doi="10.1109/NEUREL.2018.8586996",
  isbn="978-1-5386-6974-7"
}