5 citations · 6 across the 10 of their papers we have counts for
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cs.CV2025
Fast and Flexible Robustness Certificates for Semantic Segmentation
Thomas Massena, Corentin Friedrich, Franck Mamalet +1
Deep Neural Networks are vulnerable to small perturbations that can drastically alter their predictions for perceptually unchanged inputs. The literature on adversarially robust De…
cs.CV2025
Controlling False Positives in Image Segmentation via Conformal Prediction
Luca Mossina, Corentin Friedrich
Reliable semantic segmentation is essential for clinical decision making, yet deep models rarely provide explicit statistical guarantees on their errors. We introduce a simple post…
cs.CV2025★ 1 cited
Conformal Prediction for Image Segmentation Using Morphological Prediction Sets
Luca Mossina, Corentin Friedrich
Image segmentation is a challenging task influenced by multiple sources of uncertainty, such as the data labeling process or the sampling of training data. In this paper we focus o…