Abstract
The paper investigates the problem of anomaly detection in the maritime trajectory surveillance domain. Conformal predictors in this paper are used as a basis for anomaly detection. A multi-class hierarchy framework is presented for different class representations. Experiments are conducted with data taken from shipping vessel trajectories using data obtained through AIS (Automatic Identification System) broadcasts and the results are discussed.
Cite
CITATION STYLE
Smith, J., Nouretdinov, I., Craddock, R., Offer, C., & Gammerman, A. (2015). Conformal anomaly detection of trajectories with a multi-class hierarchy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9047, pp. 281–290). Springer Verlag. https://doi.org/10.1007/978-3-319-17091-6_23
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