SGP-Net improves few-shot medical image segmentation by using spectral frequency decomposition for cue disentanglement and geodesic matching on feature manifolds instead of cosine similarity.
Adnet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Beyond Euclidean Prototypes: Spectral Disentanglement and Geodesic Matching for Few-Shot Medical Image Segmentation
SGP-Net improves few-shot medical image segmentation by using spectral frequency decomposition for cue disentanglement and geodesic matching on feature manifolds instead of cosine similarity.