Detail publikace

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

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

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

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",
  annote="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.",
  address="IEEE",
  booktitle="Proceedings of the 2020 43rd International Conference on Telecommunications and Signal Processing (TSP)",
  chapter="164732",
  doi="10.1109/TSP49548.2020.9163535",
  howpublished="online",
  institution="IEEE",
  year="2020",
  month="august",
  pages="528--532",
  publisher="IEEE",
  type="conference paper"
}