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1 Ergebnisse
1
Multi-Modal Learning for Geospatial Vegetation Forecasting:
, In:
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
,
Benson, Vitus
;
Robin, Claire
;
Requena-Mesa, Christian
... - p. 27788-27799 , 2024
Link:
https://doi.org/10.1109/CVPR52733.2024.02625
RT T1 <cTitle>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)</cTitle>: T1 <Title>Multi-Modal Learning for Geospatial Vegetation Forecasting</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10656834&Exemplar=1&LAN=DE A1 Benson, Vitus A1 Robin, Claire A1 Requena-Mesa, Christian A1 Alonso, Lazaro A1 Carvalhais, Nuno A1 Cortes, Jose A1 Gao, Zhihan A1 Linscheid, Nora A1 Weynants, Melanie A1 Reichstein, Markus YR 2024 SN 2575-7075 K1 Adaptation models K1 Computer vision K1 Time series analysis K1 Vegetation mapping K1 Predictive models K1 Transformers K1 Satellite images K1 multi-modal K1 vegetation forecasting K1 geospatial K1 video prediction K1 climate change K1 early warning K1 remote sensing K1 deep learning SP 27788 OP 27799 LK http://dx.doi.org/https://doi.org/10.1109/CVPR52733.2024.02625 DO https://doi.org/10.1109/CVPR52733.2024.02625 SF ELIB - SuUB Bremen
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