# ConvLSTM-Moving-mnist
Using convlstm to prediction moving mnist dataset.
run main.py for train
1、network structure
使用其中一个序列,迭代训练,收敛。 前10帧--第11帧,...,第10-19帧预测第20帧。
输入mnist序列 三层conv 一层BasicConvLstmCel 三层conv flatten
(1,10,64,64,1) (1,10,64,64,16)(1,1,64,64,1024) (1,1,64,64,1)
2、result
![image](https://github.com/huxian0402/ConvLSTM-Moving-mnist/blob/master/label.png)
![image](https://github.com/huxian0402/ConvLSTM-Moving-mnist/blob/master/result.png)
3、loss curve
![image](https://github.com/huxian0402/ConvLSTM-Moving-mnist/blob/master/loss.png)
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ConvLSTM-Moving-mnist:使用convlstm预测运动mnist数据集
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温馨提示
ConvLSTM-Moving-mnist Using convlstm to prediction moving mnist dataset. run main.py for train 1、network structure 使用其中一个序列,迭代训练,收敛。 前10帧--第11帧,...,第10-19帧预测第20帧。 输入mnist序列 三层conv 一层BasicConvLstmCel 三层conv flatten (1,10,64,64,1) (1,10,64,64,16)(1,1,64,64,1024) (1,1,64,64,1) 2、result 3、loss curve
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