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• W3196337680 abstract "Modelling trajectory in general, and vessel trajectory in particular, is a difficult task because of the multimodal and complex nature of motion data. In this paper, we present TrAISformer-a novel deep learning architecture that can forecast vessel positions using AIS (Automatic Identification System) observations. We address the multimodality by introducing a discrete representation of AIS data and re-frame the prediction, which is originally a regression problem, as a classification problem. The model encodes complex movement patterns in AIS data in high-dimensional vectors, then applies a transformer to extract useful long-term correlations from sequences of those embeddings to sample future vessel positions. Experimental results on real, public AIS data demonstrate that TrAISformer significantly outperforms state-of-the-art methods." @default.
• W3196337680 created "2021-09-13" @default.
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• W3196337680 date "2021-09-08" @default.
• W3196337680 modified "2023-09-27" @default.
• W3196337680 title "TrAISformer-A generative transformer for AIS trajectory prediction." @default.
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