width height input depth input feature map input patches dot product with kernel output depth transformed patches output feature map output depth figure how convolut ion works note that the output width and height may differ from the input width and height they may differ for two reasonsborder effectswhich can be countered by padding the input feature map the use of strideswhich 'll define in second let' take deeper look at these notions understanding border effects and padding consider feature map ( tiles totalthere are only tiles around which you can center windowforming grid (see figure hencethe output feature map will be it shrinks littleby exactly two tiles alongside each dimensionin this case you can see this border effect in action in the earlier exampleyou start with inputswhich become after the first convolution layer licensed to