Related papers: Image patch analysis and clustering of sunspots: a…
The flows in and around sunspots are rich in detail. Starting with the Evershed flow along low-lying flow channels, which are cospatial with the horizontal penumbral magnetic fields, Evershed clouds may continue this motion at the periphery…
Sunspot-area measurements using digital images captured by two telescopes at the Mitaka campus of the National Astronomical Observatory of Japan are conducted using automated sunspot detection. A comparison between sunspot areas derived…
The emergence and decay of the sunspot groups are important components of the solar dynamo models. There are two different types of studies on the evolution of active regions. One of them is based on fewer data with higher spatial…
This paper is an overview of studying the solar features in a complex network approach. First, we introduce the structural features of complex networks and important network parameters. Applying the detrended fluctuation and rescaled range…
Sunspot numbers provide the longest continuous record of solar activity and remain a key index for heliophysical research and space-weather applications. Standard sunspot determination relies on visual inspection and algorithmic…
Previous studies have shown that the variation over the solar magnetic activity cycle of the area of facular/network features identified on broad band and narrow band imagery is positively correlated with the sunspot area and number, the…
The long term study of the Sun is necessary if we are to determine the evolution of sunspot properties and thereby inform modeling of the solar dynamo, particularly on scales of a solar cycle. We aim to determine a number of sunspot…
A satellite image is a remotely sensed image data, where each pixel represents a specific location on earth. The pixel value recorded is the reflection radiation from the earth's surface at that location. Multispectral images are those that…
A solar active region can significantly disrupt the Sun Earth space environment, often leading to severe space weather events such as solar flares and coronal mass ejections. As a consequence, the automatic classification of active region…
The volume of data being collected in solar physics has exponentially increased over the past decade and with the introduction of the $\textit{Daniel K. Inouye Solar Telescope}$ (DKIST) we will be entering the age of petabyte solar data.…
We study the visibility of sunspots and its influence on observed values of sunspot region parameters. We use Virtual Observatory tools provided by AstroGrid to analyse a sample of 6862 sunspot regions. By studying the distributions of…
We propose a new approach to interactive image segmentation based on some properties of a family of quadratic optimization problems related to dominant sets, a well-known graph-theoretic notion of a cluster which generalizes the concept of…
Context: The evolution of solar active regions is still not fully understood. The growth and decay of active regions have mostly been studied in case-by-case studies. Aims: Instead of studying the evolution of active regions case by case,…
Solar active regions (ARs) are the primary source of solar eruptions and space weather. Accurate detection and tracking of ARs is crucial for understanding their evolution and predicting solar activities. In the previous work, based on the…
Multi-view clustering has been widely used in recent years in comparison to single-view clustering, for clear reasons, as it offers more insights into the data, which has brought with it some challenges, such as how to combine these views…
We applied automatic identification of sunspot umbrae and penumbrae to daily observations from the Helioseismic Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) to study their magnetic flux (B) and area (A). The results…
In this review we give an overview about the current state-of-knowledge of the magnetic field in sunspots from an observational point of view. We start by offering a brief description of tools that are most commonly employed to infer the…
Recently, there has been growing interest in the use of machine-learning methods for predicting solar flares. Initial efforts along these lines employed comparatively simple models, correlating features extracted from observations of…
Motivated by the problem of local solar subsurface magnetic structure, we have used numerical simulation to investigate the propagation of waves through monolithic magnetic flux tubes of different size. A cluster model can be a good…
Machine learning techniques can reveal hidden structure in large data amounts and can potentially extent or even replace analytical scientific methods. In nanophotonics, modes can increase the light yield from emitters located inside the…