from another set of labels so this might be scanner a where you have training data then when you go to scanner B you actually see that you have this domain shift where your distribution of features which the network has changed I learned change because the images look slightly different and what we're trying to do here is basically try to find a way in which we can use adversarial learning to effectively help us that these images like these samples get misclassified and we instead would like to learn a classifier which is more