相关论文: Detecting and Classifying Flares in High-Resolutio…

Cloud detection is an important preprocessing step for the precise application of optical satellite imagery. In this paper, we propose a deep learning based cloud detection method named multi-scale convolutional feature fusion (MSCFF) for…

During a solar flare, it is believed that reconnection takes place in the corona followed by fast energy transport to the chromosphere. The resulting intense heating strongly disturbs the chromospheric structure, and induces complex…

This paper investigates the application of the latest machine learning technique deep neural networks for classifying road surface conditions (RSC) based on images from smartphones. Traditional machine learning techniques such as support…

Supernovae (SNe) come in various flavors and are classified into different types based on emission and absorption lines in their spectra. SN candidates are now abundant with the advent of large systematic sky surveys like the Zwicky…

The Spectrometer/Telescope for Imaging X-rays (STIX) on board Solar Orbiter (SolO) provides a unique opportunity to systematically perform stereoscopic X-ray observations of solar flares with current and upcoming X-ray missions at Earth.…

FERMI-LAT is performing an all-sky gamma-ray survey from 20 MeV to >300 GeV with unprecedented sensitivity and angular resolution. FERMI is the only mission able to detect high energy (>20 MeV) emission from the Sun during the new solar…

We conducted high dispersion spectroscopic observations of 50 superflare stars with Subaru/HDS, and measured the stellar parameters of them. These 50 targets were selected from the solar-type (G-type main sequence) superflare stars that we…

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…

In the standard model of solar eruptive events, coronal mass ejections (CMEs) and flares are associated with each other through magnetic reconnection initiated by erupting flux ropes. Observations also reveal an increasing association ratio…

Solar flares with a broadband emission in the white-light range of the electromagnetic spectrum belong to most enigmatic phenomena on the Sun. The origin of the white-light emission is not entirely understood. We aim to systematically study…

Visual inspection of solar modules is an important monitoring facility in photovoltaic power plants. Since a single measurement of fast CMOS sensors is limited in spatial resolution and often not sufficient to reliably detect small defects,…

We investigate the performance of some common machine learning techniques in identifying BHB stars from photometric data. To train the machine learning algorithms, we use previously published spectroscopic identifications of BHB stars from…

We present a novel approach to perform ground-based estimation and prediction of the surface solar irradiance with the view to predicting photovoltaic energy production. We propose the use of mini-batch k-means clustering to extract…

Solar flares stronger than X10 (S-flares, >X10) are the highest class flares which significantly impact on the Sun's evolution and space weather. Based on observations of Geostationary Orbiting Environmental Satellites (GOES) at soft X-ray…

In this paper, we study stellar light curves from the TESS satellite (Transiting Exoplanet Survey Satellite) for the presence of stellar flares. The main aim is to detect stellar flares using two-minutes cadence data and to perform…

Solar flare prediction is a central problem in space weather forecasting and has captivated the attention of a wide spectrum of researchers due to recent advances in both remote sensing as well as machine learning and deep learning…

In order to utilize solar imagery for real-time feature identification and large-scale data science investigations of solar structures, we need maps of the Sun where phenomena, or themes, are labeled. Since solar imagers produce…

We present a new analytical technique, combining Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) high-resolution imaging and spectroscopic observations, to visualize solar flare emission as a function of spectral component…

In this paper, we analyze the spectrum occupancy using different machine learning techniques. Both supervised techniques (naive Bayesian classifier (NBC), decision trees (DT), support vector machine (SVM), linear regression (LR)) and…

We study the photospheric magnetic field of ~2000 active regions in solar cycle 23 to search for parameters indicative of energy build-up and subsequent release as a solar flare. We extract three sets of parameters: snapshots in space and…