Comments (2)
Yes, the interpretation in Tab1 is correct. Generally, entropy minimization is used for semi-supervised learning. However, it could also be used for unsupervised domain adaptation, when two domains are nearly aligned. In this case, you can think of the source data together with its labels as the labeled data in the semi-supervised setting. So in practice, to use entropy minimization properly, you may want to enable it after some alignment has been performed.
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Understood, thanks for your reply!
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Related Issues (20)
- why is the resolution=1344x576 HOT 1
- Can we use FDA for faces?
- FDA and random image augmentation methods HOT 1
- label from synthia has to be convert to CityS format
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