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Found 11 papers, 2 papers with code
AI-FLARES: Artificial Intelligence for the Analysis of Solar Flares Data
AI-FLARES (Artificial Intelligence for the Analysis of Solar Flares Data) is a research project funded by the Agenzia Spaziale Italiana and by the Istituto Nazionale di Astrofisica within the framework of the ``Attivit\`a di Studio per la Comunit\`a Scientifica Nazionale Sole, Sistema Solare ed Esopianeti'' program.
Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images
The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia, i. e. a systemic loss of skeletal muscle mass and function that may be correlated to multifactorial etiological aspects.
A comprehensive theoretical framework for the optimization of neural networks classification performance with respect to weighted metrics
In many contexts, customized and weighted classification scores are designed in order to evaluate the goodness of the predictions carried out by neural networks.
Operational solar flare forecasting via video-based deep learning
Operational flare forecasting aims at providing predictions that can be used to make decisions, typically at a daily scale, about the space weather impacts of flare occurrence.
Score-oriented loss (SOL) functions
Loss functions engineering and the assessment of forecasting performances are two crucial and intertwined aspects of supervised machine learning.
Oversampling errors in multimodal medical imaging are due to the Gibbs effect
To analyse multimodal 3-dimensional medical images, interpolation is required for resampling which - unavoidably - introduces an interpolation error.
Machine learning as a flaring storm warning machine: Was a warning machine for the September 2017 solar flaring storm possible?
Machine learning is nowadays the methodology of choice for flare forecasting and supervised techniques, in both their traditional and deep versions, are becoming the most frequently used ones for prediction in this area of space weather.
Radiomics and artificial intelligence analysis of CT data for the identification of prognostic features in multiple myeloma
Multiple Myeloma (MM) is a blood cancer implying bone marrow involvement, renal damages and osteolytic lesions.
Automated Definition of Skeletal Disease Burden in Metastatic Prostate Carcinoma: a 3D analysis of SPECT/CT images
SVol was compared with the estimation of a commercial software.
Geometry of the Hough transforms with applications to synthetic data
In the framework of the Hough transform technique to detect curves in images, we provide a bound for the number of Hough transforms to be considered for a successful optimization of the accumulator function in the recognition algorithm.
A hybrid supervised/unsupervised machine learning approach to solar flare prediction
We introduce a hybrid approach to solar flare prediction, whereby a supervised regularization method is used to realize feature importance and an unsupervised clustering method is used to realize the binary flare/no-flare decision.
