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1 Ergebnisse
1
Potential of Deep Learning for Forest Height Estimation fro..:
, In:
IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
,
Carcereri, Daniel
;
Rizzoli, Paola
;
Ienco, Dino
. - p. 1481-1484 , 2023
Link:
https://doi.org/10.1109/IGARSS52108.2023.10281962
RT T1 <cTitle>IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium</cTitle>: T1 <Title>Potential of Deep Learning for Forest Height Estimation from Tandem-X Bistatic Insar Data</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10281962&Exemplar=1&LAN=DE A1 Carcereri, Daniel A1 Rizzoli, Paola A1 Ienco, Dino A1 Bruzzone, Lorenzo YR 2023 SN 2153-7003 K1 Deep learning K1 Analytical models K1 Geoscience and remote sensing K1 Estimation K1 Forestry K1 Africa K1 Convolutional neural networks K1 forest monitoring K1 forest height K1 deep learning K1 InSAR K1 TanDEM-X SP 1481 OP 1484 LK http://dx.doi.org/https://doi.org/10.1109/IGARSS52108.2023.10281962 DO https://doi.org/10.1109/IGARSS52108.2023.10281962 SF ELIB - SuUB Bremen
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