3 papers
cs.CV2026
MID: Mask-Image Distributional Divergence for Evaluating Medical Image Segmentation
Vincenzo Marcianò, Xiaoming Zhang, Gianluca Guglielmo +3
Current evaluation protocols for medical image segmentation remain largely anchored in sample-wise comparisons, e.g., Dice and Hausdorff distance, which require each prediction to…
cs.LG2026
Ranked Activation Shift for Post-Hoc Out-of-Distribution Detection
Gianluca Guglielmo, Marc Masana
State-of-the-art post-hoc out-of-distribution detection methods rely on intermediate layer activation editing. However, they exhibit inconsistent performance across datasets and mo…
cs.LG2025
Leveraging Intermediate Representations for Better Out-of-Distribution Detection
Gianluca Guglielmo, Marc Masana
In real-world applications, machine learning models must reliably detect Out-of-Distribution (OoD) samples to prevent unsafe decisions. Current OoD detection methods often rely on…