2015/04/30 by Kevin R. Moon, Veronique Delouille, Delouille Véronique +7
Computer Science · Engineering · Mathematics · Physics and Astronomy · #Advanced Image Fusion Techniques #Artificial intelligence #Astronomy #Astrophysics #Computer science #Context (archaeology) #Correlation #Geography #Geology #Geometry #Magnetic field #Magnetic flux #Magnetogram #Mathematics #Meteorology #Mount #Optical Polarization and Ellipsometry #Paleontology #Pattern recognition (psychology) #Physics #QUIET #Remote sensing #Remote-Sensing Image Classification #Solar Radiation and Photovoltaics #Solar and Space Plasma Dynamics #Space weather #Sunspot #astro-ph.SR #cs.CV
paper · pdf · doi:10.1051/swsc/2015043
published in Journal of Space Weather and Space Climate 6, A2 (EDP Open) · Accepted for publication in the Journal of Space Weather and Space Climate (SWSC). 33 pages, 12 figures
arxiv created 2015/12/10 · openalex publication_date 2016/01/01 · arxiv updated 2016/03/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31
Context. Separating active regions that are quiet from potentially eruptive ones is a key issue in Space Weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature prevents systematic studies of an active region’s evolution for example.