Publication detail

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

Type

conference paper

Language

English

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.  

Keywords

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

Authors

ŠPAŇHEL, J.; SOCHOR, J.; MAKAROV, A.

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

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"
}