首页|Study Data from University of Catania Update Understanding of Machine Learning (Cascading Machine Learning to Monitor Volcanic Thermal Activity Using Orbital Infrared Data: From Detection to Quantitative Evaluation)
Study Data from University of Catania Update Understanding of Machine Learning (Cascading Machine Learning to Monitor Volcanic Thermal Activity Using Orbital Infrared Data: From Detection to Quantitative Evaluation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on artificial intelligence have been presented. According to news originatingfrom Catania, Italy, by NewsRx correspondents, research stated, “Several satellite missions arecurrently available to provide thermal infrared data at different spatial resolutions and revisit time.”Our news journalists obtained a quote from the research from University of Catania: “Furthermore, newmissions are planned thus enabling to keep a nearly continuous ‘eye’ on thermal volcanic activity aroundthe world. This massive volume of data requires the development of artificial intelligence (AI) techniquesfor the automatic processing of satellite data in order to extract significant information about volcanoconditions in a short time. Here, we propose a robust machine learning approach to accurately detect,recognize and quantify high-temperature volcanic features using Sentinel-2 MultiSpectral Instrument (S2-MSI) imagery. We use the entire archive of high spatial resolution satellite data containing more than 6000S2-MSI scenes at ten different volcanoes around the world.”
University of CataniaCataniaItalyEuropeCyborgsEmerging TechnologiesMachine Learning
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