首页|Study Results from University of Milano Bicocca Update Understanding of Machine Learning (Assessment of Few-hits Machine Learning Classification Algorithms for Low-energy Physics In Liquid Argon Detectors)
Study Results from University of Milano Bicocca Update Understanding of Machine Learning (Assessment of Few-hits Machine Learning Classification Algorithms for Low-energy Physics In Liquid Argon Detectors)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Machine Learning are presented in a new report. According to news reporting from Milan, Italy, by NewsRx journalist s, research stated, “The physics potential of massive liquid argon TPCs in the l ow-energy regime is still to be fully reaped because few-hits events encode info rmation that can hardly be exploited by conventional classification algorithms. Machine learning (ML) techniques give their best in these types of classificatio n problems.” Funders for this research include Universita degli Studi di Milano - Bicocca wit hin the CRUI-CARE Agreement, CERN through the CERN QTI, Horizon Marie Sklodowska -Curie actions, Ministry of Education, Universities and Research (MIUR).
MilanItalyEuropeAlgorithmsArgonCyborgsEmerging TechnologiesMachine LearningUniversity of Milano Bicocca
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