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SIKORA, P. KIAC, M. DUTTA, M.
Originální název
Classification of railway level crossing barrier and light signalling system using YOLOv3
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
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.
Klíčová slova
object detection; railway level crossing barrier; train; traffic light; yolo
Autoři
SIKORA, P.; KIAC, M.; DUTTA, M.
Vydáno
11. 8. 2020
Nakladatel
IEEE
Místo
Milan, Italy
ISBN
978-1-7281-6376-5
Kniha
Proceedings of the 2020 43rd International Conference on Telecommunications and Signal Processing (TSP)
Strany od
528
Strany do
532
Strany počet
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" }