Conformal Anomaly Detection of Trajectories with a Multi-class Hierarchy. / Smith, James; Nouretdinov, Ilia; Craddock, Rachel; Offer, Charles; Gammerman, Alex.
Statistical Learning and Data Sciences: Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings. ed. / Alex Gammerman; Vladimir Vovk; Harris Papadopoulos. Springer, 2015. p. 281-290 (Lecture Notes in Computer Science; Vol. 9047).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Published
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.
| Original language | English |
|---|---|
| Title of host publication | Statistical Learning and Data Sciences |
| Subtitle of host publication | Third International Symposium, SLDS 2015, Egham, UK, April 20-23, 2015, Proceedings |
| Editors | Alex Gammerman, Vladimir Vovk, Harris Papadopoulos |
| Publisher | Springer |
| Pages | 281-290 |
| Number of pages | 10 |
| ISBN (Electronic) | 978-3-319-17091-6 |
| ISBN (Print) | 978-3-319-17090-9 |
| DOIs | |
| Publication status | Published - 3 Apr 2015 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 9047 |
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
ID: 24468132