Paper

Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation

A deep learning model trained on some labeled data from a certain source domain generally performs poorly on data from different target domains due to domain shifts. Unsupervised domain adaptation methods address this problem by alleviating the domain shift between the labeled source data and the unlabeled target data... (read more)

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