9 citations · 9 across the 1 of their papers we have counts for
4 papers
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations
Gelu Nita, Manolis Georgoulis, Irina Kitiashvili +38
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicis…
Machine-learning approach to identification of coronal holes in solar disk images and synoptic maps
Egor Illarionov, Alexander Kosovichev, Andrey Tlatov
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 f…
Segmentation of coronal holes in solar disk images with a convolutional neural network
E. Illarionov, A. Tlatov
Current coronal holes segmentation methods typically rely on image thresholding and require non-trivial image pre- and post-processing. We have trained a neural network that accura…
Not quite unreasonable effectiveness of machine learning algorithms
Egor Illarionov, Roman Khudorozhkov
State-of-the-art machine learning algorithms demonstrate close to absolute performance in selected challenges. We provide arguments that the reason can be in low variability of the…