Training deep convolution regression network with multi dimensional output
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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.
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Gautham Sholingar
le 16 Mai 2017
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
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