RDAOT: Robust Unsupervised Deep Sub-Domain Adaptation Through Optimal Transport for Image Classification
In traditional machine learning, the training and testing data are assumed to come from the same independent and identical distributions. This assumption, however, does not hold up in real-world applications, as differences between the training and testing data may have different distributions. Doma...
Tallennettuna:
| Päätekijät: | , , , |
|---|---|
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
IEEE
2023-01-01
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| Sarja: | IEEE Access |
| Aiheet: | |
| Linkit: | https://ieeexplore.ieee.org/document/10246279/ |
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