Presents the first unsupervised source-free framework for ranking semantic and instance segmentation models via prediction consistency under perturbations, with rankings correlating to target-domain performance across 2D/3D biomedical tasks.
Tune it the Right Way: Un- supervised Validation of Domain Adaptation via Soft Neigh- borhood Density, 2021
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Unsupervised Source-Free Ranking of Biomedical Segmentation Models Under Distribution Shift
Presents the first unsupervised source-free framework for ranking semantic and instance segmentation models via prediction consistency under perturbations, with rankings correlating to target-domain performance across 2D/3D biomedical tasks.