Study on the Efficiency of Video Scene Detection Based on YOLO Series

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Study on the Efficiency of Video Scene Detection Based on YOLO Series

Shen, Yue / Yan, Han / Zhang, Yuwei / Xie, Zhengyu

The safety of high-speed railway operation in 2021 Beijing Winter Olympics puts forward higher requirements for the speed and accuracy of detecting foreign body intrusion on the high-speed railway. Based on the sampling data of the severe weather of high-speed railway cameras, this paper builds a network and uses empirical weights to explore the efficiency of the most widely used YOLO series algorithms. Besides, we use 16380 images as the testing data set to test the speed and accuracy of detecting algorithms, trying to find the best method to give us the real-time detecting results and meet emergencies promptly, which has profound significance both socially and economically.

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Dokumentinformationen

Titel :

Study on the Efficiency of Video Scene Detection Based on YOLO Series

Weitere Titelangaben:

Lect. Notes Electrical Eng.

Beteiligte:

Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Liang, Jianying (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Shen, Yue (Autor:in) / Yan, Han (Autor:in) / Zhang, Yuwei (Autor:in) / Xie, Zhengyu (Autor:in)

Kongress:

International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021

Erschienen in:

Proceedings of the 5th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 2021 ; Kapitel : 64 ; 575-581

Lecture Notes in Electrical Engineering ; 868

Erscheinungsdatum :

2022-02-23

Format / Umfang :

7 pages

ISBN :

978-981-16-9913-9 , 978-981-16-9912-2

ISSN :