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Author:

Wang, Yazi (Wang, Yazi.) | Feng, Yuehong (Feng, Yuehong.) | Sun, Huaibo (Sun, Huaibo.)

Indexed by:

EI Scopus SCIE

Abstract:

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.

Keyword:

Intelligence Algorithm improvement Vehicle positioning Wireless positioning Convolutional neural network

Author Community:

  • [ 1 ] [Wang, Yazi]ZhouKou Normal Univ, Sch Math & Stat, Zhoukou 466001, Henan, Peoples R China
  • [ 2 ] [Feng, Yuehong]Beijing Univ Technol, Coll Appl Sci, Beijing 100022, Peoples R China
  • [ 3 ] [Sun, Huaibo]Fuyang Normal Univ, Sch Math & Stat, Fuyang 466001, Henan, Peoples R China

Reprint Author's Address:

  • [Sun, Huaibo]Fuyang Normal Univ, Sch Math & Stat, Fuyang 466001, Henan, Peoples R China

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Source :

NEURAL COMPUTING & APPLICATIONS

ISSN: 0941-0643

Year: 2020

Issue: 14

Volume: 33

Page: 8131-8141

6 . 0 0 0

JCR@2022

ESI Discipline: ENGINEERING;

ESI HC Threshold:115

Cited Count:

WoS CC Cited Count: 3

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

Affiliated Colleges:

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