A hierarchical framework fuses a long-term intent predictor with a grid-based Spatio-Temporal Graph Transformer and environmental cross-modal attention to cut average displacement error by 25% over 10-hour horizons on Australian vessel data.
A transformer network with sparse aug- mented data representation and cross entropy loss for ais-based vessel trajectory prediction
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Hierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction
A hierarchical framework fuses a long-term intent predictor with a grid-based Spatio-Temporal Graph Transformer and environmental cross-modal attention to cut average displacement error by 25% over 10-hour horizons on Australian vessel data.