Comments (2)
Hi @GeorgeBatch - when developing UNI, we also tried pathology-specific mean and standardization parameters. We did not find a meaningful difference in performance in linear probing and evaluation when using the mean/standard deviation normalization for the Mass-1K dataset. As long as all patch features are extracted using the same norm, the impact on downstream evaluation should be minimal.
As the other baselines in this study such as CTransPath also used ImageNet norm, we opted for ImageNet for ease-of-use and simplicity.
from uni.
Thank you for your explanation!
from uni.
Related Issues (20)
- Results of the PANDA Competition HOT 1
- Label for IDH1 mutation prediction
- How to use UNI for segmentation task? HOT 3
- How was figure 3e generated in the paper? HOT 2
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- Model weights result in nan-values for half precision HOT 1
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- Release trained model on SegPath data
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from uni.