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1 Ergebnisse
1
Learnable Variational Models for the Reconstruction of Sea ..:
, In:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
,
Benaichouche, S.
;
Goff, C. Le
;
Boussidi, B.
.. - p. 6821-6824 , 2022
Link:
https://doi.org/10.1109/IGARSS46834.2022.9883870
RT T1
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
: T1
Learnable Variational Models for the Reconstruction of Sea Surface Currents Using Ais Data Streams: A Case Study on the Sicily Channel
UL https://suche.suub.uni-bremen.de/peid=ieee-9883870&Exemplar=1&LAN=DE A1 Benaichouche, S. A1 Goff, C. Le A1 Boussidi, B. A1 Rousseau, F. A1 Fablet, R. YR 2022 SN 2153-7003 K1 Deep learning K1 Sea surface K1 Surface reconstruction K1 Radar remote sensing K1 Inverse problems K1 Supervised learning K1 Sea measurements K1 Sea surface currents K1 data assimilation K1 variational learning K1 HF Radar SP 6821 OP 6824 LK http://dx.doi.org/https://doi.org/10.1109/IGARSS46834.2022.9883870 DO https://doi.org/10.1109/IGARSS46834.2022.9883870 SF ELIB - SuUB Bremen
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