[1]熊群芳,林 军,刘 悦,等.深度学习研究现状及其在轨道交通领域的应用[J].控制与信息技术(原大功率变流技术),2018,(02):1-6.[doi:10.13889/j.issn.2096-5427.2018.02.001]
 XIONG Qunfang,LIN Jun,LIU Yue,et al.Deep Learning and Its Application in the Field of Rail Transit[J].High Power Converter Technology,2018,(02):1-6.[doi:10.13889/j.issn.2096-5427.2018.02.001]
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深度学习研究现状及其在轨道交通领域的应用()
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《控制与信息技术》(原《大功率变流技术》)[ISSN:2095-3631/CN:43-1486/U]

卷:
期数:
2018年02期
页码:
1-6
栏目:
综述·评论
出版日期:
2018-04-05

文章信息/Info

Title:
Deep Learning and Its Application in the Field of Rail Transit
文章编号:
2096-5427(2018)02-0001-06
作者:
熊群芳林 军刘 悦袁 浩游 俊
(中车株洲电力机车研究所有限公司,湖南 株洲 412001)
Author(s):
XIONG Qunfang LIN Jun LIU Yue YUAN Hao YOU Jun
( CRRC Zhuzhou Institute Co., Ltd., Zhuzhou, Hunan 412001, China )
关键词:
深度学习轨道交通车道线检测故障检测
Keywords:
deep learning rail transportation lane detection vehicle equipment fault detection
分类号:
TP399
DOI:
10.13889/j.issn.2096-5427.2018.02.001
文献标志码:
A
摘要:
深度学习在特征提取与图像识别方面有巨大的潜力和优势,近年来其在轨道交通领域的应用研究受到了越来越多的关注。文章详细介绍了深度学习在司机身份识别、疲劳检测、车道线检测以及车辆设备故障检测等方面的应用研究现状,总结了其在轨道交通领域应用中的主要作用和存在的问题,并展望了其未来值得研究的方向。
Abstract:
Deep learning has shown great potential and advantage in feature extraction and image recognition. In recent years, more and more researches have focused on the application of deep learning in rail transit. It introduced the current state of deep learning and its application in the field of rail transit, including identification, driver fatigue detection, lane detection and vehicle recognition equipment fault detection. Additionally, it summarized the main functions and existing problems of deep learning in the field of rail transit, and presented some prospects of future work.

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备注/Memo

备注/Memo:
收稿日期:2017-11-28
作者简介:熊群芳(1990-),女,设计师,主要从事图像处理方面的研究工作。
更新日期/Last Update: 2018-04-26