Research on vehicle intelligent wireless location algorithm based on convolutional neural network

Vehicle positioning and vehicle identification of natural scene images are an important part of intelligent transportation systems and unmanned driving research. In current situation, there are still some problems in vehicle intelligent wireless positioning. In order to improve the intelligent wirel...

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Bibliographic Details
Published in:Neural computing & applications Vol. 33; no. 14; pp. 8131 - 8141
Main Authors: Wang, Yazi, Feng, Yuehong, Sun, Huaibo
Format: Journal Article
Language:English
Published: London Springer London 01.07.2021
Springer Nature B.V
Subjects:
Algorithms
Artificial Intelligence
Artificial neural networks
Autonomous cars
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Image Processing and Computer Vision
Intelligent transportation systems
Machine learning
Neural networks
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
Transportation networks
Vehicle identification
Vehicle positioning
Intelligence
Convolutional neural network
Algorithm improvement
Wireless positioning
ISSN:0941-0643, 1433-3058
Online Access:Get full text
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Summary:Vehicle positioning and vehicle identification of natural scene images are an important part of intelligent transportation systems and unmanned driving research. In current situation, there are still some problems in vehicle intelligent wireless positioning. In order to improve the intelligent wireless positioning efficiency of vehicles, based on the convolutional neural network, this research combines the concept of deep learning to carry out algorithm innovation in the research. Moreover, this paper combines the actual vehicle positioning problem points to collect data, simulates the vehicle positioning situation in a variety of complex situations, and designs a controlled test to verify. The results show that the algorithm of this study has certain effects, which can provide reference for subsequent related research and has certain practical significance.
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content type line 14
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-020-04911-w