
SEA-ViT, an advanced deep learning model, integrates Vision Transformer (ViT) and bidirectional Gated Recurrent Units (GRUs) to capture complex spatio-temporal dependencies and improve the accuracy of sea surface currents forecasting.


coremsg

enhancing-sea-surface-currents-forecasting-with-vision-transformer-and-spatio-temporal-covariance-modeling


Enhancing Sea Surface Currents Forecasting with Vision Transformer and Spatio-Temporal Covariance Modeling
