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Conformal Anomaly Detection of Trajectories with a Multi-class Hierarchy

机译:具有多类层次结构的轨迹的共形异常检测

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摘要

The paper investigates the problem of anomaly detection in the maritime trajectory surveillance domain. Conformal predictors in this paper are used as a basis for anomaly detection. A multi-class hierarchy framework is presented for different class representations. Experiments are conducted with data taken from shipping vessel trajectories using data obtained through AIS (Automatic Identification System) broadcasts and the results are discussed.
机译:本文研究了海上航迹监测领域的异常检测问题。本文中的保形预测变量用作异常检测的基础。提供了用于不同类表示的多类层次结构框架。使用通过AIS(自动识别系统)广播获得的数据,对从船舶航迹中获取的数据进行实验,并对结果进行了讨论。

著录项

  • 来源
  • 会议地点 Egham(GB)
  • 作者单位

    Computer Learning Research Center, Royal Holloway University of London, Egham, UK;

    Computer Learning Research Center, Royal Holloway University of London, Egham, UK;

    Thales UK, London, UK;

    Thales UK, London, UK;

    Computer Learning Research Center, Royal Holloway University of London, Egham, UK;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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  • 入库时间 2022-08-26 14:06:23

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