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Predicted class weights from the teacher network for two IPB configurations, as well as the actual training dataset distribution. The multi-scale input patches from multi-label images (ML+MS) allows the teacher to learn a more accurate distribution of the image classes, which it can then use to provide the student with a more accurate pseudo-balanced dataset.
