Related papers: A Robust Deep Learning Framework for Prominence De…
Atmospheric environments favorable for lightning and convection are commonly represented by proxies or parameterizations based on expert knowledge such as CAPE, wind shears, charge separation, or combinations thereof. Recent developments in…
We present coordinated coronal observations of the August 21, 2017 total solar eclipse with the Airborne Infrared Spectrometer (AIR-Spec) and the Extreme-ultraviolet Imaging Spectrometer (EIS). These instruments provide an unprecedented…
We propose a model for solar prominences based on converging flow observed in the chromosphere and photosphere. In contrast with existing models we do not apply a shearing motion along the neutral line. Instead we assume that bipolar loops…
Now a days, UAVs such as drones are greatly used for various purposes like that of capturing and target detection from ariel imagery etc. Easy access of these small ariel vehicles to public can cause serious security threats. For instance,…
We use The Sun Watcher with Active Pixel System detector and Image Processing (SWAP) imager onboard the Project for Onboard Autonomy 2 (PROBA2) mission to study the evolution of large-scale EUV structures in the solar corona observed…
Dense plasma fragments were observed to fall back on the solar surface by the Solar Dynamics Observatory after an eruption on 7 June 2011, producing strong EUV brightenings. Previous studies investigated impacts in regions of weak magnetic…
Reliable photovoltaic defect identification is essential for maintaining energy yield, ensuring warranty compliance, and enabling scalable inspection of rapidly expanding solar fleets. Although recent advances in computer vision have…
A forward model is described in which we synthesize spectra from an ab-initio 3D MHD simulation of an outer stellar atmosphere, where the coronal heating is based on braiding of magnetic flux due to photospheric footpoint motions. We…
A number of industrial applications, such as smart grids, power plant operation, hybrid system management or energy trading, could benefit from improved short-term solar forecasting, addressing the intermittent energy production from solar…
To study and monitor the Sun and its atmosphere, various space missions have been launched in the past decades. With the rapid improvement in technology and different mission requirements, the data products are subject to constant change.…
Triggering process for prominence instability and consequent CMEs is not fully understood. Prominences are maintained by the Lorentz force against the gravity, therefore reduction of the prominence mass due to the coronal rain may cause the…
The paper presents a reliable method using deep learning to recognize solar filaments in H-alpha full-disk solar images automatically. This method cannot only identify filaments accurately but also minimize the effects of noise points of…
Transits of habitable planets around solar-like stars are expected to be shallow, and to have long periods, which means low information content. The current bottleneck in the detection of such transits is caused in large part by the…
The triggering process for coronal mass ejections (CME) in the solar atmosphere is not fully understood. We use observations from different spacecraft at several wavelengths to detect an instability process for a prominence/filament with a…
Satellite imagery is important for many applications including disaster response, law enforcement, and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the…
This report presents the results of the DeepSolaris project that was carried out under the ESS action 'Merging Geostatistics and Geospatial Information in Member States'. During the project several deep learning algorithms were evaluated to…
As the role played by statistical and computational sciences in climate and environmental modelling and prediction becomes more important, Machine Learning researchers are becoming more aware of the relevance of their work to help tackle…
Constraining the frequency of energy deposition in magnetically-closed active region cores requires sophisticated hydrodynamic simulations of the coronal plasma and detailed forward modeling of the optically-thin line-of-sight integrated…
The existing approaches for salient motion segmentation are unable to explicitly learn geometric cues and often give false detections on prominent static objects. We exploit multiview geometric constraints to avoid such shortcomings. To…
In this study, we examine the associations between channel features and convolutional kernels during the processes of feature purification and gradient backpropagation, with a focus on the forward and backward propagation within the…