I see! Thanks!



 mfcs:

But, in the case of Cross Entropy Loss…does it make sense for the target to be a matrix, in which the elements are the values ​​of the color bins (classes) that have the highest probability, that for each pixel and the CNN’s output to be a tensor with 313 layers , in which each pixel has a probability distribution? Would Cross Entropy Loss calculate the error correctly?





 ptrblck:

This sounds like a classical segmentation use case and should be possible.


But how the Cross entropy Loss perform the computation between a probability distribution and a class value instead of the probability of the class?