9 citations · 17 across the 3 of their papers we have counts for
5 papers
A novel approach to the classification of terrestrial drainage networks based on deep learning and preliminary results on Solar System bodies
Carlo Donadio, Massimo Brescia, Alessia Riccardo +3
Several approaches were proposed to describe the geomorphology of drainage networks and the abiotic/biotic factors determining their morphology. There is an intrinsic complexity of…
Astroinformatics based search for globular clusters in the Fornax Deep Survey
Giuseppe Angora, Massimo Brescia, Stefano Cavuoti +15
In the last years, Astroinformatics has become a well defined paradigm for many fields of Astronomy. In this work we demonstrate the potential of a multidisciplinary approach to id…
Neural Gas based classification of Globular Clusters
Giuseppe Angora, Massimo Brescia, Stefano Cavuoti +3
Within scientific and real life problems, classification is a typical case of extremely complex tasks in data-driven scenarios, especially if approached with traditional techniques…
Data Deluge in Astrophysics: Photometric Redshifts as a Template Use Case
Massimo Brescia, Stefano Cavuoti, Valeria Amaro +4
Astronomy has entered the big data era and Machine Learning based methods have found widespread use in a large variety of astronomical applications. This is demonstrated by the rec…
Astrophysical Data Analytics based on Neural Gas Models, using the Classification of Globular Clusters as Playground
Giuseppe Angora, Massimo Brescia, Giuseppe Riccio +3
In Astrophysics, the identification of candidate Globular Clusters through deep, wide-field, single band HST images, is a typical data analytics problem, where methods based on Mac…