like we're getting get the details right at the noise pixels so and you could also imagine optimizing to different versions of the loss one version of the losses using the mean squared error and the other words for the loss is using a binary signal across central P loss and both both are equally good and endless it makes more sense to use the cross entropy loss but the mean square error loss is also very likely to work well if as long as you let it train with the right set of hyper parameters so stack denoising auto-encoder is basically the