The application of machine learning in solar physics has the potential to greatly enhance our
understanding of the complex processes that take place in the atmosphere of the Sun. By …

This review summarizes popular unsupervised learning methods, and gives an overview of
their past, current, and future uses in astronomy. Unsupervised learning aims to organise the …

Context. Precise localization and characterization of active regions (AR) and coronal holes
(CH) as observed by extreme ultra violet (EUV) imagers are crucial for a wide range of solar …

In Fall 2008 NASA selected a large international consortium to produce a comprehensive
automated feature-recognition system for the Solar Dynamics Observatory (SDO). The SDO …

This review presents a comprehensive and systematic overview of image-processing
techniques that are used in automated feature-detection algorithms applied to solar data: i) …

Context. The study of the variability of the solar corona and the monitoring of coronal holes,
quiet sun and active regions are of great importance in astrophysics as well as for space …

Region of interest segmentation in solar images is the subject of frequent research in solar
physics. This study outlines watershed by immersion segmentation to identify coronal hole …

With explosive growth of the astronomical data, astronomy has become a representative
data-rich discipline so as to defy traditional research methodologies and paradigm to …

Solar eruptive events could affect radio communication, global positioning systems, and
some high-tech equipment in space. Active regions on the Sun are the main source regions …

The solar corona is the origin of very dynamic events that are mostly produced in active
regions (AR) and coronal holes (CH). The exact location of these large-scale features can …