AndrewNg's CNN notes (1X1 conv1)

1X1 convolution and its applications (1) & (2)

1 x 1 convolution is also named a Network in Network. You can think it as a dimension reduction technique which can easily generate a deeper network without conventional way of stacking layers via applying bunch of different filters.

Here two usages are described.

(1) Motivation for inception network, which leads to the construction of much more complex structure of GoogLeNet!

 (2) to save the computation cost by first do 1x1 conv (x16) then conv 5x5 with 32 times instead of directly from 28X28X192 to 28X28X32, just consuming 1/10 of time/computation resource(as illustrated in bottom right)