Artificial intelligence spots coronal holes to automate space weather prediction
Scientists from the University of Graz (Austria), Skoltech and their colleagues from the US and Germany have developed a new neural network that can reliably detect coronal holes from space-based observations. This application paves the way for more reliable space weather predictions and provides valuable information for the study of the solar activity cycle. The paper was published in the journal Astronomy & Astrophysics.
phys.org
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