• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Trends in Ecology & Evolution >Research on Road Traffic Situation Awareness System Based on Image Big Data
【24h】

Research on Road Traffic Situation Awareness System Based on Image Big Data

机译：基于图像大数据的道路交通状况认识系统研究

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Road traffic is an important component of the national economy and social life. Promoting intelligent and Informa ionization construction in the field of road traffic is conducive to the construction of smart cities and the formulation of macro strategies and construction plans for urban traffic development. Aiming at the shortcomings of the current road traffic system, this article, on the basis of combining convolution neural network, situational awareness technology, database and other technologies, takes the road traffic situational awareness system as the research object, and analyzes the information collection, processing, and analysis process of road traffic situational awareness system. Convolutional neural networks (CNN), region-CNN (R-CNN), fast R-CNN, and faster R-CNN are used for vehicle class classification and location identification in road image big data. The deep convolutional neural network model based on road traffic image big data was further established, and the system requirements analysis and system framework design and implementation were carried out. Through the analysis and trial of actual cases, the results show the application effect of the realized road traffic situational awareness system, which provides a scientific reference and basis for the establishment of modern intelligent transportation system.
机译：道路交通是国民经济和社会生活的重要组成部分。促进道路交通领域的智能和信息电离建设有利于智能城市的建设以及城市交通发展宏观策略和施工计划的制定。旨在目前道路交通系统的缺点，本文在组合卷积神经网络，情境意识技术，数据库等技术的基础上，将道路交通态势意识系统作为研究对象，并分析了信息收集，道路交通态势认识系统的处理和分析过程。卷积神经网络（CNN），区域-CNN（R-CNN），FAST R-CNN和更快的R-CNN用于路线图像大数据中的车辆类分类和位置识别。进一步建立了基于道路交通图像大数据的深度卷积神经网络模型，进行了系统需求分析和系统框架设计和实现。通过实际情况的分析和试验，结果表明了实现的道路交通态势意识系统的应用效果，为建立现代智能交通系统提供了科学的参考和基础。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号