Metric learning for domain adversarial network

1 Introduction The existing domain adaptation methods[1,2]always aim to perform domain alignment between the source and target domain to alleviate the problem of domain shift[3].The target domain samples are likely to scatter on the classification boundary due to a lack of label information.Therefore,how to identify these overlapping classes in the target domain,called easily-confused classes,becomes the key to the improvement of classification performance.