Machine-learning Approach to Identification of Coronal Holes in Solar Disk Images and Synoptic Maps

  title={Machine-learning Approach to Identification of Coronal Holes in Solar Disk Images and Synoptic Maps},
  author={E. A. Illarionov and Alexander G. Kosovichev and Andrey Tlatov},
  journal={The Astrophysical Journal},
Identification of solar coronal holes (CHs) provides information both for operational space weather forecasting and long-term investigation of solar activity. Source data for the first problem are typically from the most recent solar disk observations, while for the second problem it is convenient to consider solar synoptic maps. Motivated by the idea that the concept of CHs should be similar for both cases we investigate universal models that can learn CH segmentation in disk images and… 

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Magnetohydrodynamics of the Sun (Cambridge University Press).

  • 2014

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