Thanks so much for your response! Will take a look.

Thanks so much for your response! Does temperature scaling change the relative ordering of the probabilities?

Thanks so much for your response! Is temperature scaling the go-to calibration method I should try? Does temperature scaling change the relative ordering of the probabilities?

Thanks so much for your response! Are you aware of any calibration methods I could try? Preferably ones which won't to long to implement / incorporate :P

Thanks so much for your response! Are you aware of any calibration methods I could try? Preferably ones which won't take long to implement / incorporate :P

I'm not sure I understand. Are you suggesting I normalize each pixel in each NxN label-map to be mean 0 and std of 1? And then use this normalized label-map during training?

Thanks for your response -- This is an interesting idea! Unfortunately, I am actually training my network to predict 1000+ classes, for which such an idea would be computationally intractable...

Thanks so much for your response!

This makes sense. Are you aware of any techniques that can be used to make these probabilities comparable?

I understand that the outputs shouldn't necessarily be treated as probabilities. I simply want a relative ordering of the pixels in terms of "likelihood."