Maritime anomaly detection: A review-Reference-Cited by-同舟云学术

Maritime anomaly detection: A review

Published:2018-05-25 Issue:5 Volume:8 Page:
ISSN:1942-4787
Container-title:WIREs Data Mining and Knowledge Discovery
language:en
Short-container-title:WIREs Data Mining Knowl Discov

Author:

Riveiro Maria¹,Pallotta Giuliana²,Vespe Michele³

Affiliation:

1. School of InformaticsUniversity of SkövdeSkövdeSweden

2. Lawrence Livermore National LaboratoryLivermoreCaliforniaUS

3. Directorate for Space, Security and Migration, Demography, Migration & Governance UnitEuropean Commission, Joint Research Centre (JRC)IspraItaly

Funder

The Knowledge Foundation

Publisher

Wiley

Subject

General Computer Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/widm.1266

Reference168 articles.

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2. Estimated Time of Arrival Using Historical Vessel Tracking Data

3. Power to the People: The Role of Humans in Interactive Machine Learning

4. Anneken M. Fischer Y. &Beyerer J.(2015). Evaluation and comparison of anomaly detection algorithms in annotated datasets from the maritime domain.2015 SAI Intelligent Systems Conference(IntelliSys) 169–178.

5. Maritime Traffic Networks: From historical positioning data to unsupervised maritime traffic monitoring;Arguedas V.;IEEE Transactions on Intelligent Transportation Systems,2017

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