In the "LE-UDA: Label-Efficient Unsupervised Domain Adaptation for Medical Image Segmentation" paper, it is rightly mentioned that target labels are not available for hyperparameter selection.
I just want to clarify how you perform checkpoint selection. Am I correct that you create fake target images to obtain a proxy measure for assessing the expected performance for the real images target images?
If so, did you by any chance compare this approach to supervised checkpoint selection? I.e. using labels from the target domain?
In the "LE-UDA: Label-Efficient Unsupervised Domain Adaptation for Medical Image Segmentation" paper, it is rightly mentioned that target labels are not available for hyperparameter selection.
I just want to clarify how you perform checkpoint selection. Am I correct that you create fake target images to obtain a proxy measure for assessing the expected performance for the real images target images?
If so, did you by any chance compare this approach to supervised checkpoint selection? I.e. using labels from the target domain?