Normalization before or after resizing I'm training deep learning network using images (to be exact - I'm solving semantic segmentation problem).

What's the proper order of resizing (I need to resize images to fixed width X height) and normalization (dividing by 255 value) of images in preprocessing?

Does it make more sense to do first resizing and then normalization? Or first normalization and then resizing?
Resize and then normalize, that's the only pipeline that makes sense.

If you resize after normalization, depending on the resize algorithm, you may end up with values that are outside of the normalized range.