4 citations · 6 across the 3 of their papers we have counts for
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cs.CV2023★ 4 cited
Reduction of rain-induced errors for wind speed estimation on SAR observations using convolutional neural networks
Aurélien Colin, Pierre Tandeo, Charles Peureux +2
Synthetic Aperture Radar is known to be able to provide high-resolution estimates of surface wind speed. These estimates usually rely on a Geophysical Model Function (GMF) that has…
cs.CV2022★ 1 cited
Rain regime segmentation of Sentinel-1 observation learning from NEXRAD collocations with Convolution Neural Networks
Aurélien Colin, Pierre Tandeo, Charles Peureux +3
Remote sensing of rainfall events is critical for both operational and scientific needs, including for example weather forecasting, extreme flood mitigation, water cycle monitoring…