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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 un...
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| Publicado no: | Med Image Comput Comput Assist Interv |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7202929/ https://ncbi.nlm.nih.gov/pubmed/32377643 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-32245-8_29 |
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