Name
Title | ||
|---|---|---|
Uncertainty-Aware Recurrent Encoder-Decoder Networks for Vessel Trajectory Prediction |
Abstract | ||
|---|---|---|
In this paper, we propose a deep learning framework for sequence-to-sequence vessel trajectory prediction based on encoder-decoder recurrent neural networks to learn the predictive distribution of maritime patterns from historical Automatic Identification System data and sequentially generate future trajectory estimates given previous observations. Special focus is given on modeling the predictive... |
Year | Venue | Keywords |
|---|---|---|
2021 | 2021 IEEE 24th International Conference on Information Fusion (FUSION) | Deep learning,Uncertainty,Recurrent neural networks,Monte Carlo methods,Computational modeling,Computer architecture,Predictive models |
DocType | ISBN | Citations |
Conference | 978-1-7377497-1-4 | 1 |
PageRank | References | Authors |
0.35 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samuele Capobianco | 1 | 1 | 0.35 |
| Nicola Forti | 2 | 1 | 0.35 |
| Leonardo M. Millefiori | 3 | 1 | 0.35 |
| Paolo Braca | 4 | 1 | 0.69 |
| Peter Willett | 5 | 10 | 1.61 |