RETRACTED ARTICLE: Intelligent traffic monitoring and traffic diagnosis analysis based on neural network algorithm

Traffic sign recognition and lane detection play an important role in traffic flow planning, avoiding traffic accidents, and alleviating traffic chaos. At present, the traffic intelligent recognition rate still needs to be improved. In view of this, based on the neural network algorithm, this study...

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Veröffentlicht in:Neural computing & applications Jg. 33; H. 14; S. 8107 - 8117
Hauptverfasser: Wang, Yantao, Wang, Quan, Suo, Daxiang, Wang, Tiezheng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Springer London 01.07.2021
Springer Nature B.V
Schlagworte:
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Image Processing and Computer Vision
Probability and Statistics in Computer Science
S. I : Intelligent Computing Methodologies in Machine learning for IoT Applications
Special Issue on Intelligent Computing Methodologies in Machine learning for IoT Applications
Intelligent transportation
Neural network algorithm
Intelligent detection
Abnormal recognition
Intelligent diagnosis
ISSN:0941-0643, 1433-3058
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Zusammenfassung:Traffic sign recognition and lane detection play an important role in traffic flow planning, avoiding traffic accidents, and alleviating traffic chaos. At present, the traffic intelligent recognition rate still needs to be improved. In view of this, based on the neural network algorithm, this study constructs an intelligent transportation system based on neural network algorithm, and combines machine vision technology to carry out intelligent monitoring and intelligent diagnosis of traffic system. In addition, this study discusses in detail the core of the monitoring system: multi-target tracking algorithm, and introduces the complete implementation process and details of the system, and highlights the implementation and tracking effect of the multi-target tracker. Finally, this study uses case identification to analyze the effectiveness of the algorithm proposed by this paper. The research results show that the proposed method has certain practical effects and can be used as a reference for subsequent system construction.
Bibliographie:ObjectType-Correction/Retraction-1
SourceType-Scholarly Journals-1
content type line 14
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-020-04899-3