《All convolutional neural networks for radar-based precipitation nowcasting》论文解读
这篇文章于2019年1月在Procedia Computer Science上发表。它的贡献在于选择和采用了合适的数据预处理方法和损失函数，提出了网络模型——Dozhdya.Net。 数据 在介绍模型之前首先说一下该实验所采用的数据。数据名为RY，其测量范围为 900 ∗ 900 k m 900*900km 900∗900km，它的空间和时间的分辨率分别为 1 ∗ 1 k m 1*1km 1∗1k
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相关文章
- 1. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting论文阅读
- 2. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
- 3. 论文阅读：《Convolutional Neural Networks for Sentence Classification》
- 4. 《Convolutional Neural Networks for Sentence Classification》论文研读
- 5. 论文阅读-Fast Algorithms for Convolutional Neural Networks
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- 9. 《SmaAt-UNet Precipitation Nowcasting using a Small Attention-UNet Architecture》论文解读
- 10. 论文《Convolutional Neural Networks for Sentence Classification》总结