Learning to Adapt to Label-Scarce Image Domain via Angular Distance-Based Feature Alignment
Most recent domain adaptation (DA) methods deal with unsupervised setup, which requires numerous target images for training. However, constructing a large-scale image set of the target domain is occasionally much harder than preparing a smaller number of image and label pairs. To cope with the probl...
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9907019/ |