我把内核和过滤器搞混了。

Question

我读了一篇文章，作者使用CNN，方案如下：

-----------------

Input image 30*30 => Feature maps => Feature maps =>  Feature maps => Feature maps
                       28 * 28          14*14            12*12            6*6
-----------------
            Filtring 5*3*3   downsampling 2*2    Filtring 5*3*3   downsampling 2*2 

根据我的理解，我们有两个滤波器5* 3，最后3个对应于通道RGB SO3，对吗？

Answer 1

这意味着你有5个通道(意味着5个过滤器/内核)的3x3。

Answer 2

What they are trying to say is that:

First:
the conv is being done using 5 different 3x3 2d kernels
input 30x30 ==> output 5 different 28x28

Second:
max pool 2x2 ie the output dim becomes halved
input 28x28 ==> output 14x14

Third:
the conv is being done using 5 different 3x3 2d kernels
input 14x14 ==> output 5 different 12x12

Lastly:
max pool 2x2 ie the output dim becomes halved
input 12x12 ==> output 6x6