相关论文: Automatic Detection of Occulted Hard X-ray Flares …

In modern astrophysics, the machine learning has increasingly gained more popularity with its incredibly powerful ability to make predictions or calculated suggestions for large amounts of data. We describe an application of the supervised…

RHESSI measurements relevant to the fundamental processes of energy release and particle acceleration in flares are summarized. RHESSI's precise measurements of hard X-ray continuum spectra enable model-independent deconvolution to obtain…

We report a NuSTAR observation of a solar microflare, SOL2015-09-01T04. Although it was too faint to be observed by the GOES X-ray Sensor, we estimate the event to be an A0.1 class flare in brightness. This microflare, with only 5 counts…

A deep learning network, Long-Short Term Memory (LSTM) network, is used in this work to predict whether the maximum flare class an active region (AR) will produce in the next 24 hours is class $\Gamma$. We considered $\Gamma$ are $\ge M$,…

To solve a number of problems in solar physics related to mechanisms of energy release in solar corona parameters of hot coronal plasma are required, such as energy distribution, emission measure, differential emission measure, and their…

In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…

X-radiation from energetic electrons is the prime diagnostic of flare-accelerated electrons. The observed X-ray flux (and polarization state) is fundamentally a convolution of the cross-section for the hard X-ray emission process(es) in…

The aim of the present paper is to use quasi-periodic oscillations in hard X-rays (HXRs) of solar flares as a diagnostic tool for investigation of impulsive electron acceleration. We have selected a number of flares which showed…

Given the rarity of significant solar flares compared to smaller ones, training effective machine learning models for solar activity forecasting is challenging due to insufficient data. This study proposes using generative deep learning…

Around the peaks of substantial flares, bright artifact nearly horizontal saturation streaks (B-streaks) corresponding to the brightest parts of the flare sources appear in the STEREO/EUVI 195 A images. We show that the length of such…

We investigated the three-dimensional (3D) magnetic structures and dynamics responsible for particle acceleration in an X7.1-class flare that occurred on October 1, 2024, in NOAA active region 13842. We combined stereoscopic hard X-ray…

Non-intrusive inspection systems based on X-ray radiography techniques are routinely used at transport hubs to ensure the conformity of cargo content with the supplied shipping manifest. As trade volumes increase and regulations become more…

Fermi-LAT >30 MeV observations have increased the number of detected solar flares by almost a factor of 10 with respect to previous space observations. These sample both the impulsive and long duration phases of GOES M and X class flares.…

The analysis of waves in the visible side of the Sun allows the detection of active regions in the farside through local helioseismology techniques. The knowledge of the magnetism in the whole Sun, including the non-visible hemisphere, is…

Heatmap regression (HR) has become one of the mainstream approaches for face alignment and has obtained promising results under constrained environments. However, when a face image suffers from large pose variations, heavy occlusions and…

We apply classical machine vision and machine deep learning methods to prototype signal classifiers for the search for extraterrestrial intelligence. Our novel approach uses two-dimensional spectrograms of measured and simulated radio…

In machine learning, the term active learning regroups techniques that aim at selecting the most useful data to label from a large pool of unlabelled examples. While supervised deep learning techniques have shown to be increasingly…

This paper presents an novel object type classification method for automotive applications which uses deep learning with radar reflections. The method provides object class information such as pedestrian, cyclist, car, or non-obstacle. The…

Whilst the most dynamic solar active regions (ARs) are known to flare frequently, predicting the occurrence of individual flares and their magnitude, is very much a developing field with strong potentials for machine learning applications.…

Solar flare hard X-rays (HXRs) are produced as bremsstrahlung when an accelerated population of electrons interacts with the dense chromospheric plasma. HXR observations presented by using the Ramaty High-Energy Solar Spectroscopic Imager…