CAMPI , C.

In this paper we present a Hough Transform-based method for the detection of the spinal district in X-ray Computed Tomography (CT) images in order to build binary masks that can be applied to functional images to infer information on the metabolic activity of the spinal marrow. This kind of information may be of particular interest for the...

Loss functions engineering and the assessment of prediction performances are two crucial and inter-twined aspects of supervised machine learning. This paper focuses on binary classification to introduce a class of loss functions that are defined on probabilistic confusion matrices and that allow an automatic and a priori maximization of the...

Machine learning is now one of the methodologies of choice for flare forecasting, and supervised techniques, in both their traditional and deep versions, are becoming more frequently used for prediction in this area of space weather. Most studies assess the prediction effectiveness of machine-learning methods by computing confusion matrices,...