Machine learning has achieved remarkable success in many applications. However,
existing studies are largely based on the closed-world assumption, which assumes that the …

Deep learning (DL) models have provided state-of-the-art performance in various medical
imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) …

This paper presents a probabilistic framework to obtain both reliable and fast uncertainty
estimates for predictions with Deep Neural Networks (DNNs). Our main contribution is a …

A false negative in object detection describes an object that was not correctly localised and
classified by a detector. In concurrent work, we introduced five'false negative mechanisms' …

The failure of object detection algorithms usually refers to the inaccuracy, inefficiency, or
inapplicability of previously performing algorithms in specific problems or scenarios …

Bien qu'il ait été démontré que les modèles d'apprentissage en profondeur (DL)
fonctionnent très bien sur diverses tâches d'imagerie médicale, l'inférence en présence de …