%0 Journal Article %1 journals/aeog/LiLXFZLMCYY22 %A Li, Jingbo %A Li, Changchun %A Xu, Weimeng %A Feng, Haikuan %A Zhao, Fa %A Long, Huiling %A Meng, Yang %A Chen, Weinan %A Yang, Hao %A Yang, Guijun %D 2022 %J Int. J. Appl. Earth Obs. Geoinformation %K dblp %P 102818 %T Fusion of optical and SAR images based on deep learning to reconstruct vegetation NDVI time series in cloud-prone regions. %U http://dblp.uni-trier.de/db/journals/aeog/aeog112.html#LiLXFZLMCYY22 %V 112

@article{journals/aeog/LiLXFZLMCYY22, added-at = {2024-01-08T00:00:00.000+0100}, author = {Li, Jingbo and Li, Changchun and Xu, Weimeng and Feng, Haikuan and Zhao, Fa and Long, Huiling and Meng, Yang and Chen, Weinan and Yang, Hao and Yang, Guijun}, biburl = {https://www.bibsonomy.org/bibtex/2284754cef600593010510e8b6d739583/dblp}, ee = {https://doi.org/10.1016/j.jag.2022.102818}, interhash = {474e0074a1d0245376ff07d4aacd54fc}, intrahash = {284754cef600593010510e8b6d739583}, journal = {Int. J. Appl. Earth Obs. Geoinformation}, keywords = {dblp}, pages = 102818, timestamp = {2024-04-09T02:20:29.000+0200}, title = {Fusion of optical and SAR images based on deep learning to reconstruct vegetation NDVI time series in cloud-prone regions.}, url = {http://dblp.uni-trier.de/db/journals/aeog/aeog112.html#LiLXFZLMCYY22}, volume = 112, year = 2022 }