CNN for ordinal classification How do we design a CNN for ordinal classification?
I am trying to analyze plant leaf images for diseases. I've got the disease type classification working. Now we need to classify the magnitude of the disease affliction on a scale of 1 to 10 (ordinal scale), where 1 is almost no trace of diseased parts on the leaf and 10 is completely diseased.

Is it possible to construct a CNN for this task?

How do I deal with the imbalance in training samples for each ordinal level?
NN aren't ideal for regression tasks.

I'd train 10 networks, one for each magnitude.

CNN #k would be a binary classifier predicting whether the magnitude is k or less

In other words, CNN #10 is a function that always returns 1, and CNN#0 is the binary classifier you've already trained.