Publication detail

Classification of railway level crossing barrier and light signalling system using YOLOv3

SIKORA, P. KIAC, M. DUTTA, M.

Original Title

Classification of railway level crossing barrier and light signalling system using YOLOv3

Type

conference paper

Language

English

Original Abstract

Nowadays, the world is experiencing an increasing boom in deep learning. This is more and more used in many areas such as medicine, robotics, industry, security systems, etc. This article deals with the detection and classification of railway barriers at level crossings, railway warnings, and light signaling systems. The evaluation system uses cameras, which are suitably positioned to capture the entire scene at a given railway level crossing. The detection itself is done using image processing techniques and deep neural networks. The proposed system uses the GPU acceleration to achieve real-time capability.

Keywords

object detection; railway level crossing barrier; train; traffic light; yolo

Authors

SIKORA, P.; KIAC, M.; DUTTA, M.

Released

11. 8. 2020

Publisher

IEEE

Location

Milan, Italy

ISBN

978-1-7281-6376-5

Book

Proceedings of the 2020 43rd International Conference on Telecommunications and Signal Processing (TSP)

Pages from

528

Pages to

532

Pages count

5

URL

https://ieeexplore.ieee.org/document/9163535

BibTex

@inproceedings{BUT164732,
  author="Pavel {Sikora} and Martin {Kiac} and Malay Kishore {Dutta}",
  title="Classification of railway level crossing barrier and light signalling system using YOLOv3",
  booktitle="Proceedings of the 2020 43rd International Conference on Telecommunications and Signal Processing (TSP)",
  year="2020",
  pages="528--532",
  publisher="IEEE",
  address="Milan, Italy",
  doi="10.1109/TSP49548.2020.9163535",
  isbn="978-1-7281-6376-5",
  url="https://ieeexplore.ieee.org/document/9163535"
}