9 citations · 17 across the 5 of their papers we have counts for
6 papers · 1 filter
Leveraging Transfer Learning for Astronomical Image Analysis
Stefano Cavuoti, Lars Doorenbos, Demetra De Cicco +7
The exponential growth of astronomical data from large-scale surveys has created both opportunities and challenges for the astrophysics community. This paper explores the possibili…
Strengthening leverage of Astroinformatics in inter-disciplinary Science
Massimo Brescia, Giuseppe Angora
Most domains of science are experiencing a paradigm shift due to the advent of a new generation of instruments and detectors which produce data and data streams at an unprecedented…
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…