Get Started: DCGAN for Fashion-MNIST

Get Started: DCGAN for Fashion-MNIST

Get Started: DCGAN for Fashion-MNIST – PyImageSearch

“The paper suggests using batch normalization (batchnorm) in both G and D to help stabilize GAN training. Batchnorm standardizes the input layer to have a zero mean and unit variance. It’s typically added after the hidden layer and before the activation layer. As we progress in the GAN series, you will learn better normalization techniques for GANs. For now, we will stay with the DCGAN paper recommendation of using batchnorm…”

Source: www.pyimagesearch.com/2021/11/11/get-started-dcgan-for-fashion-mnist/