Empirical Validation of Conformal Prediction for Trustworthy Skin Lesions Classification

arXiv:2312.07460v2 Announce Type: replace-cross
Abstract: Background and objective: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisions by providing complementary information, particularly within high-risk applications. existing studies have explored various methods that often operate under specific assumptions or necessitate substantial modifications to the network architecture to effectively account for uncertainties. The objective of this paper is to study Conformal Prediction, an emerging distribution-free uncertainty quantification technique, and provide …

abstract applications arxiv assumptions classification cs.cv decisions eess.iv information pivotal prediction quantification risk robust studies systems trustworthy type uncertainty validation