Learning Convolutional Neural Networks Backpropagation
Posted songyuc
tags:
篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了Learning Convolutional Neural Networks Backpropagation相关的知识,希望对你有一定的参考价值。
1 致谢
感谢大佬的文章《Convolutional Neural Networks backpropagation: from intuition to derivation》,写的很清楚!
2 介绍
在这篇文章中,我们将跟随知乎文章《卷积神经网络(CNN)反向传播算法推导·南柯一梦宁沉沦》来学习Convolution的Backpropagation计算;
CNN卷积介绍
CNN中的卷积实际上是点积互相关(Dot Products);
在进行推导之前,我们首先对符号进行定义,定义第
l
l
l层的输出为
z
x
,
y
l
=
W
l
∗
V
+
b
z_x,y^l = \\bmW^l\\ast \\bmV + \\bmb
zx,yl=Wl∗V+b
3 卷积运算的反向传播
首先
以上是关于Learning Convolutional Neural Networks Backpropagation的主要内容,如果未能解决你的问题,请参考以下文章
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
[论文理解] Learning Efficient Convolutional Networks through Network Slimming
文献阅读18期:Learning Convolutional Neural Networks for Graphs
文献阅读18期:Learning Convolutional Neural Networks for Graphs
文献阅读18期:Learning Convolutional Neural Networks for Graphs
论文阅读之Convolutional Knowledge Tracing: Modeling Individualization in Student Learning Process