Deep learning-based object detection between train and rail transit platform door Online publication date: Fri, 14-Oct-2022
by Fen Cheng; Hao Cai
International Journal of Grid and Utility Computing (IJGUC), Vol. 13, No. 5, 2022
Abstract: When the train is running, if foreign objects are stuck between the platform tracks, it will often cause huge safety accidents. Therefore, based on deep learning, this paper designs a wide-gap outdoor platform foreign object detection system to detect foreign objects between rail transit platform doors and trains. The main design idea of the system is to explore the real environment of the subway, create a virtual experimental environment, design the hardware equipment of the detection system, and obtain video images captured under various weather and lighting conditions through image analysis and processing. The research results show that the system designed in this paper can well detect the influence of pedestrians getting on and off and intermediate objects when the train stops at the platform, and the detection accuracy of large objects can reach 100%.
Online publication date: Fri, 14-Oct-2022
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Grid and Utility Computing (IJGUC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email email@example.com