The smaller kernel size,applied in VGG,is proved to be effective in capturing rich context information,We also use
larger kernel to cover a large region in a tensor. Instead of using a 5X5 kernel ,we can use kernel size= (5,1) and (1,5) cascaded conv layer  or use two 3x3 conv layer cascadely.Both methods can reduce the computatioanl comsuption. What’s the difference?  Is there any disadvantage of  using 2 conv layers?