文献类型：会议论文

英文题名：Indoor intelligent driving scene-based traffic signal data set

作者：Fu, En[1,2]; Pan, Weiguo[1,2]; Pan, Feng[2]; Yang, Qing[2]

第一作者：Fu, En

通讯作者：Pan, Weiguo

机构：[1] Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, 100101, China; [2] College of Robotics, Beijing Union University, Beijing, 100101, China

第一机构：北京联合大学北京市信息服务工程重点实验室

会议论文集：2020 International Conference on Data Processing Algorithms and Models, ICDPAM 2020

会议日期：December 4, 2020 - December 6, 2020

会议地点：Xiamen, China

语种：英文

外文关键词：Data handling - Deep learning - Engineering education - Learning systems - Traffic signs

摘要：In recent years, with the rapid development of intelligent driving technology, vision based traffic signal target detection is one of the urgent problems to be solved; especially with the extensive application of deep learning technology, the traffic signal data set is more and more important. Due to the variety of traffic signals, there is no data set that can cover all categories at home and abroad. This paper presents a traffic signal data set based on indoor traffic scene. The currently disclosed data category includes 22 categories, including traffic signs and traffic lights. Simultaneously, this paper also uses a two-stage deep learning method to conduct experiments. In order to facilitate other researchers to conduct further research on the disclosed data set in this paper. ? Published under licence by IOP Publishing Ltd.