Joceline Hinz

A Critical Synthesis of Uncertainty Quantification and Foundation Models for Semantic Segmentation

This is the first systematic evaluation of UQ methods applied to a foundation model for semantic segmentation and highlights both the promise and the current limitations of uncertainty-aware foundation models, pointing to the need for future work that jointly optimizes accuracy, robustness, and efficiency for real-world deployment.