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1 Ergebnisse
1
Recurrent Neural Networks for Modelling Gross Primary Produ..:
, In:
IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
,
Montero, David
;
Mahecha, Miguel D.
;
Martinuzzi, Francesco
... - p. 4214-4217 , 2024
Link:
https://doi.org/10.1109/IGARSS53475.2024.10640715
RT T1 <cTitle>IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium</cTitle>: T1 <Title>Recurrent Neural Networks for Modelling Gross Primary Production</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10640715&Exemplar=1&LAN=DE A1 Montero, David A1 Mahecha, Miguel D. A1 Martinuzzi, Francesco A1 Aybar, Cesar A1 Klosterhalfen, Anne A1 Knohl, Alexander A1 Koebsch, Franziska A1 Anaya, Jesus A1 Wieneke, Sebastian YR 2024 SN 2153-7003 K1 Radar remote sensing K1 Recurrent neural networks K1 Laser radar K1 Atmospheric measurements K1 Ultraviolet sources K1 Biological system modeling K1 Production K1 Gross Primary Production K1 Recurrent Neural Networks K1 Remote Sensing K1 XAI K1 Climate Extremes SP 4214 OP 4217 LK http://dx.doi.org/https://doi.org/10.1109/IGARSS53475.2024.10640715 DO https://doi.org/10.1109/IGARSS53475.2024.10640715 SF ELIB - SuUB Bremen
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