Training deep convolution regression network with multi dimensional output

I'm taking in an input image of 512x512 and running it through an alexnet type architecture. The output needs to be another image. The image can be arranged as either [512pixels, 512pixels,1channel,N number of examples] or as [262144,N]. Niether of them are working. The trainNetwork function is being used. Any help you could provide would be greatly appreciated.

Answer 1

[Gautham Sholingar]

1) Could you share some of your code to explain how you are setting up the neural network?

2) Is there a specific error you notice when you try to run the 'trainNetwork' function?

3) Have you had a chance to look at some of the shipped examples which explain how to use an 'm by m by 1' channel image dataset for training a network? Run the following command in the MATLAB command window to look at the example which shows this:

>> openExample('nnet/UseDataInImageDatastoreForTrainingCNNExample')

The following documentation link explains this example: https://www.mathworks.com/help/nnet/ref/trainnetwork.html#bvg3o5h-1