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A deep learning-based imputation method for missing gaps in..:
Liu, Ning
;
Li, Yi
;
Zang, Zengliang
...
Atmospheric Environment. 325 (2024) - p. 120440 , 2024
Link:
https://doi.org/10.1016/j.atmosenv.2024.120440
RT Journal T1
A deep learning-based imputation method for missing gaps in satellite aerosol products by fusing numerical model data
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.atmosenv.2024.120440&Exemplar=1&LAN=DE A1 Liu, Ning A1 Li, Yi A1 Zang, Zengliang A1 Hu, Yiwen A1 Fang, Xin A1 Lolli, Simone PB Elsevier BV YR 2024 SN 1352-2310 JF Atmospheric Environment VO 325 SP 120440 LK http://dx.doi.org/https://doi.org/10.1016/j.atmosenv.2024.120440 DO https://doi.org/10.1016/j.atmosenv.2024.120440 SF ELIB - SuUB Bremen
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