Prediction of the GNSS station coordinates

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Reference

Publications

[1] Kiani Shahvandi, M., & Soja, B. (2021, July). Modified Deep Transformers for GNSS Time Series Prediction. In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 8313-8316). IEEE. https://doi.org/10.1109/IGARSS47720.2021.9554764

[2] Kiani Shahvandi, M., & Soja, B. (2021, October). Small Geodetic Datasets and Deep Networks: Attention-Based Residual LSTM Autoencoder Stacking for Geodetic Time Series. In International Conference on Machine Learning, Optimization, and Data Science (pp. 296-307). Springer, Cham. https://doi.org/10.1007/978-3-030-95467-3_22

[3] Ruttner, P., Hohensinn, R., D’Aronco, S., Wegner, J. D., & Soja, B. (2021). Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach. Remote Sensing, 14(1), 17. https://doi.org/10.3390/rs14010017