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Home > Science Articles > Peer Reviewed Articles > SunSCC: segmenting, grouping and classifying sunspots from ground-based observations using deep learning
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2023
Ref: SCART-2023-0149

SunSCC: segmenting, grouping and classifying sunspots from ground-based observations using deep learning

Sayez, Niels ; De Vleeschouwer, Christophe ; Delouille, Veronique ; Bechet, Sabrina ; Lefèvre, Laure


submitted to Space Weather (2023)


Keyword(s): We automatically detect, cluster, and classify sunspots using ground-based white light observations and deep learning methods. ; Our method achieves comparable results to those obtained in the literature on space-based continuum and magnetogram observations. ; Ensembles of classifiers are effective in discriminating reliable and likely erroneous predictions on the sunspot classification.
Funding: B2 /191/P2/DeepSun


The record appears in these collections:
Royal Observatory of Belgium > Solar Physics & Space Weather (SIDC)
Science Articles > Peer Reviewed Articles
Solar-Terrestrial Centre of Excellence



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 Record created 2023-05-02, last modified 2023-05-02
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