000006458 001__ 6458
000006458 005__ 20240228164126.0
000006458 0247_ $$2DOI$$a10.1029/2023JA031548
000006458 037__ $$aSCART-2023-0149
000006458 100__ $$aSayez, Niels
000006458 245__ $$aSunSCC: segmenting, grouping and classifying sunspots from ground-based observations using deep learning
000006458 260__ $$c2023
000006458 536__ $$aB2 /$$c191/$$fP2/DeepSun
000006458 594__ $$aSTCE
000006458 6531_ $$aWe automatically detect, cluster, and classify sunspots using ground-based white light observations and deep learning methods.
000006458 6531_ $$aOur method achieves comparable results to those obtained in the literature on space-based continuum and magnetogram observations. 
000006458 6531_ $$aEnsembles of classifiers are effective in discriminating reliable and likely erroneous predictions on the sunspot classification.
000006458 700__ $$aDe Vleeschouwer, Christophe
000006458 700__ $$aDelouille, Veronique
000006458 700__ $$aBechet, Sabrina
000006458 700__ $$aLefèvre, Laure
000006458 773__ $$n12$$pJournal of Geophysical Research: Space Physics$$v128
000006458 8560_ $$fveronique.delouille@observatoire.be
000006458 905__ $$apublished in
000006458 980__ $$aREFERD