How can I train a convolutional neural network for both classification and regression?
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I would like to use the same convolutional neural network to classify and perform regression on images. In other words, I would like to have shared input and hidden layers, but then branch off into a regression output layer and a classification output layer. How can I do this?
Part of this problem is that I have a lot of float-valued images stored as .mat files, so I would like to use their file names instead of storing all of my data in memory. Is it possible to use an image datastore with 2 labels for each image, or something like it?