《SmaAt-UNet Precipitation Nowcasting using a Small Attention-UNet Architecture》論文解讀
這是一篇通過卷積神經網絡預測降水的文章。一直以來，專家們通過數值天氣預報(NWP)的方式預測降水，但這種方法很難利用過去的時刻信息，且需要大量的數學計算和時間需求。因此，作者提出了一種數據驅動的神經網絡用於降水預報。過去在深度學習方面，預測降水之前更多用的是RNN模型，如ConvLSTM，TrajGRU等模型，這些模型有着存儲記憶的門單元，能對過去的時序信息有記憶功能。另一種用於預測的模型是一
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- 1. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting論文閱讀
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