when you move to the new domain because it looks so different from what the model was trained on domain adaptation algorithms try to smooth out that gap and the domain adverse oral approach is based on training a feature extractor where the features have the same statistics regardless of which domain you extracted them on so in the domain adversarial game you have one player that's a feature extractor and another player that's a domain recognizer the domain recognizer wants to look at the output of the feature extractor and