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 ...

We propose an encoder-decoder for open-vocabulary semantic segmentation comprising a hierarchical encoder-based cost map generation and a gradual fusion decoder. We introduce a category early ...

Abstract: Recent deep learning methods for vessel trajectory prediction are able to learn complex maritime patterns from historical automatic identification system (AIS) data and accurately predict ...