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Real-Time Maritime Traffic Anomaly Detection Based on Sensors and History Data Embedding

The automated identification system of vessel movements receives a huge amount of multivariate, heterogeneous sensor data, which should be analyzed to make a proper and timely decision on vessel movements. The large number of vessels makes it difficult and time-consuming to detect abnormalities, thu...

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Опубликовано в: :Sensors (Basel)
Главные авторы: Venskus, Julius, Treigys, Povilas, Bernatavičienė, Jolita, Tamulevičius, Gintautas, Medvedev, Viktor
Формат: Artigo
Язык:Inglês
Опубликовано: MDPI 2019
Предметы:
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC6749247/
https://ncbi.nlm.nih.gov/pubmed/31480449
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s19173782
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