Exploring autoregression patterns for automatic vessel type classification-Reference-Cited by-同舟云学术

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Exploring autoregression patterns for automatic vessel type classification

Published:2023-12-09 Issue: Volume: Page:
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Ferreira Martha Dais,Sadeghi Zahra,Matwin Stan

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-023-05826-8.pdf

Reference35 articles.

1. Abdallah NB, Iphar C, Arcieri G, et al (2019) Fixing errors in the ais destination field. In: OCEANS 2019 - Marseille, pp 1–5, https://doi.org/10.1109/OCEANSE.2019.8867139

2. Brandoli B, Raffaetà A, Simeoni M, et al (2022) From multiple aspect trajectories to predictive analysis: a case study on fishing vessels in the northern adriatic sea. GeoInformatica pp 1–29

3. Cai J, Chen G, Lützen M et al (2021) A practical ais-based route library for voyage planning at the pre-fixture stage. Ocean Eng 236(109):478. https://doi.org/10.1016/j.oceaneng.2021.109478

4. CM B (2010) Bishop pattern recognition and machine learning

5. d’Afflisio E, Braca P, Millefiori LM et al (2018) Detecting anomalous deviations from standard maritime routes using the ornstein-uhlenbeck process. IEEE Trans Signal Process 66(24):6474–6487. https://doi.org/10.1109/TSP.2018.2875887

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