Inferring Latent Domains for Unsupervised Deep Domain Adaptation
Unsupervised Domain Adaptation (UDA) refers to the problem of learning a model in a target domain where labeled data are not available by leveraging information from annotated data in a source domain. Most deep UDA approaches operate in a single-source, single-target scenario, i.e., they assume that...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 43(2021), 2 vom: 26. Feb., Seite 485-498
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| 1. Verfasser: |
Mancini, Massimiliano
(VerfasserIn) |
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| Weitere Verfasser: |
Porzi, Lorenzo,
Bulo, Samuel Rota,
Caputo, Barbara,
Ricci, Elisa |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2021
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article
Research Support, Non-U.S. Gov't |
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