[1]袁航,钟发海,聂上上,等.基于卷积神经网络的道路拥堵识别研究[J].郑州大学学报(工学版),2019,40(02):21-25.
 LUO Ronghui,YUAN Hang,ZHONG Fahai,et al.The Research of Traffic Jam Detection Based on Convolutional Neural Network[J].Journal of Zhengzhou University (Engineering Science),2019,40(02):21-25.
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基于卷积神经网络的道路拥堵识别研究()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
40
期数:
2019年02期
页码:
21-25
栏目:
出版日期:
2019-03-19

文章信息/Info

Title:
The Research of Traffic Jam Detection Based on Convolutional Neural Network
作者:
袁航钟发海聂上上罗荣辉
Author(s):
LUO RonghuiYUAN HangZHONG FahaiNIE Shangshang
文献标志码:
A
摘要:
本文针对城市道路日益严峻的拥堵问题,依据道路拥堵快速检测技术对缓解堵车问题的应用价值,结合深度学习和图像处理技术,提出了一种基于卷积神经网络的道路拥堵检测方式。此方式相对于传统机器视觉方法,无需前期提取道路背景,不受光照亮度和实际环境的影响,具有识别速度快、占用计算资源少、泛化性好等特点。现已在实际项目中得以应用,并取得了较好的效果
Abstract:
  In order to solove the increasingly serious congestion problem of urban roads ,a road congestion dectection method based on convolutional neural network was proposed in this paper.This method was based on the appliciation value of road congestion rapid detection technology to alleviate the traffic jam promblem.Besides,it combined deep learning with image processing  technology.Compared with traditional methods,this method did not need to extract the background in the early stage, and was not affected by the illumination brightness and the actual environment.It had the characteristics of fasrt recognition speed,less ocupied comoutong resources and good generalization. It has been applied in practical projects and achieved good results.
更新日期/Last Update: 2019-03-24