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dc.contributor.advisor杨晨晖
dc.contributor.author成超
dc.date.accessioned2018-12-05T01:48:04Z
dc.date.available2018-12-05T01:48:04Z
dc.date.issued2018-01-02
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/170581
dc.description.abstract智能交通系统的建设与运行,可以提升交通服务质量和交通设施的运行效率,保障交通安全,减少交通拥堵。交通场景感知技术是智能交通系统的重要技术之一。基于视频的交通事件检测技术,已经发展出较为丰富的成果,并在工程中发挥较好的作用;但是,其在夜间等特殊场景下的鲁棒性还有待继续提升。其实,很多的交通视频监控工程都提供有音频信息,但是音频数据没有在交通事件检测中得到充分的利用。本文针对交通场景智能感知的需求特点,研究融合视频信息和音频信息的目标识别、事件检测等技术,有望提升交通场景的智能感知能力,进而提升智能交通系统的综合管控性能。 本文首先对现有的视听觉融合感知技术相关理论进行了比较全面系统的梳理,探讨...
dc.description.abstractThe construction and operation of Intelligent Transportation System can improve the quality of traffic service and the efficiency of traffic facilities, ensure traffic safety and reduce traffic congestion. The traffic scene perception technology is one of the most important technologies in Intelligent Transportation System. Video-based traffic event detection technology has developed a lot of achi...
dc.language.isozh_CN
dc.relation.urihttps://catalog.xmu.edu.cn/opac/openlink.php?strText=58751&doctype=ALL&strSearchType=callno
dc.source.urihttps://etd.xmu.edu.cn/detail.asp?serial=61052
dc.subject视听觉融合
dc.subject交通场景感知
dc.subject智能交通系统
dc.subject机器学习
dc.subject深度学习
dc.subjectAudio-Visual Fusion
dc.subjectTraffic Scene Perception
dc.subjectIntelligent Transportation System
dc.subjectMachine Learning
dc.subjectDeep Learning
dc.title视听觉融合的交通场景智能感知技术研究
dc.title.alternativeResearch on Traffic Scene Intelligent Sensing Technology based on Audio-Visual Fusion
dc.typethesis
dc.date.replied2017-05-15
dc.description.note学位:工学硕士
dc.description.note院系专业:信息科学与技术学院_计算机科学与技术
dc.description.note学号:23020141153144


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