Question regarding normalization input


When the Unet is trained, the input is normalized and with the mean and std of this input, the target is also normalized. Why do you do this? I am making a neural network that circumvents the Inverse fast Fourier transform (IFFT), so that you can just use one big neural network on the masked images. However, I don’t know what to do with the normalization of the images, since it happens right after the IFFT. Maybe you can help me out?

Hi @Jan_Huiskes ,

The normalization helps stabilize training but is not required. When evaluating the reconstructions they need to be unnormalized to the original scale anyway, (see: