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- pre-processing type SWDocumentation assertion.
- pre-processing type Resource assertion.
- pre-processing type MediaObject assertion.
- pre-processing description "n maritime traffic surveillance, detecting illegal activities, such as illegal fishing or transhipment of illicit products is a crucial task of the coastal administration. In the open sea, one has to rely on Automatic Identification System (AIS) messages transmitted by on-board transponders, which are captured by surveillance satellites. However, insincere vessels often intentionally shut down their AIS transponders to hide illegal activities. In the open sea, it is very challenging to differentiate intentional AIS shutdowns from missing reception due to protocol limitations, bad weather conditions or restricting satellite positions. This paper presents a novel approach for the detection of abnormal AIS missing reception based on self-supervised deep learning techniques and transformer models. Our method can process AIS messages in real-time, in particular, more than 500 Millions AIS messages per month, corresponding to the trajectories of more than 60 000 ships. The method is evaluated on 1-year of real-world data coming from four Norwegian surveillance satellites. The results show that the method can detect confirmed real-world intentional AIS shutdown operations." assertion.
- pre-processing dateCreated "2022-10-05 13:38:39.041164+00:00" assertion.
- pre-processing name "Detecting Intentional AIS Shutdown in Open Sea Maritime Surveillance Using Self-Supervised Deep Learning" assertion.
- pre-processing contentUrl "https://gitlab.com/simula_ais_message/pre-processing" assertion.
- pre-processing creator 0000-0002-1784-2920 assertion.
- pre-processing dateModified "2022-10-05 13:38:39.630828+00:00" assertion.
- pre-processing license no-permission assertion.
- pre-processing sdDatePublished "2022-10-05 13:38:39.041164+00:00" assertion.
- pre-processing author 0000-0002-1784-2920 assertion.