论文标题
使用Geotracknet从AIS数据中检测异常血管行为：从实验室到海洋
Detection of Abnormal Vessel Behaviours from AIS data using GeoTrackNet: from the Laboratory to the Ocean
论文作者
论文摘要
海上交通的不断增长导致需要自动异常检测，这引起了极大的研究关注。 AIS（自动识别系统）数据提供的信息以及最新的深度学习进展，使使用神经网络（NNS）的船只监测成为一种非常有前途的方法。本文分析了我们最近引入的有关操作环境的新型神经网络-Geotracknet。特别是，我们旨在评估（i）Geotracknet在专家解释方面检测到的异常行为的相关性，（ii）GeotRackNet可以实时处理AIS数据流的程度。我们报告实验表明满足模型运营水平的高潜力。
The constant growth of maritime traffic leads to the need of automatic anomaly detection, which has been attracting great research attention. Information provided by AIS (Automatic Identification System) data, together with recent outstanding progresses of deep learning, make vessel monitoring using neural networks (NNs) a very promising approach. This paper analyses a novel neural network we have recently introduced -- GeoTrackNet -- regarding operational contexts. Especially, we aim to evaluate (i) the relevance of the abnormal behaviours detected by GeoTrackNet with respect to expert interpretations, (ii) the extent to which GeoTrackNet may process AIS data streams in real time. We report experiments showing the high potential to meet operational levels of the model.
