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Fine-tuning deep models in a new domain can require a significant\namount of data, which for many applications is simply not available. We propose\na new CNN architecture which introduces an adaptation layer and an additional\ndomain confusion loss, to learn a representation that is both semantically\nmeaningful and domain invariant. 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