Synthetic Source Universal Domain Adaptation through Contrastive Learning
Universal domain adaptation (UDA) is a crucial research topic for efficient deep learning model training using data from various imaging sensors. However, its development is affected by unlabeled target data. Moreover, the nonexistence of prior knowledge of the source and target domain makes it more...
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| Format: | article |
| Langue: | EN |
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MDPI AG
2021
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| Accès en ligne: | https://doaj.org/article/7a576453521840dfb764b12bf8684110 |
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