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esd.copernicus.org
| | gmd.copernicus.org
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| | Abstract. Forecasting heavy precipitation accurately is a challenging task for most deep learning (DL)-based models. To address this, we present a novel DL architecture called multi-scale feature fusion (MFF) that can forecast precipitation with a lead time of up to 3?h. The MFF model uses convolution kernels with varying sizes to create multi-scale receptive fields. This helps to capture the movement features of precipitation systems, such as their shape, movement direction, and speed. Additionally, the...
| | www.hydrology-and-earth-system-sciences.net
0.4 parsecs away

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| | elifesciences.org
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| | www.lucasnotes.com
26.0 parsecs away

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| SQL Server DBA notes about databases, programming, system administration, and troubleshooting.