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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...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749247/ https://www.ncbi.nlm.nih.gov/pubmed/31480449 http://dx.doi.org/10.3390/s19173782 |