Why it's so that in convolutional neural networks we generally take the image dimensions of input image to be generally a square? We even do padding to make it happen. Why not different dimensions?What I understood is that computer computes multiplication and division (by 2) much faster than the rest.Can someone shed some light on this? Any link or reference will be appreciated. I already have CS231n notes and lecture slides. 
Why CNN input images are often square shaped?
neural network;deep learning;convolution