What are Pooling Layers in Deep Neural Networks?

[@salihalbayrak-es8ky]

finally someone explaining pooling. congrats sir, youre the gigachad of the year

[@deeplearningexplained]

Glad it was useful 😅

[@thouys9069]

I still don't get why it's supposed to help translational invariance. As you say, the convolution is already capable of that. If I move the image contents 50 pixels to the right, the features should also move 50 pixels, given stride 1 and padding. Exactly the same is true for traditional sobel edge detectors. The edges don't change if I convolve the image with the edge detection filters translated or not

[@deeplearningexplained]

No the convolution help with translational equivariance, but not with translational invariance. The idea of adding pooling is that you are forcing exact nearby pixel/feature information to be “lost”. This means that the network is forced to learn more generalizeable components of the picture you are showing it.