Related papers: Application and interpretation of deep learning fo…

Current coronal mass ejection (CME) models set their lower boundary to be in the lower corona. They do not calculate accurately the transfer of free magnetic energy from the convection zone to the magnetically dominated corona because they…

Aims. Although the temporal evolution of active regions (ARs) is relatively well understood, the processes involved continue to be the subject of investigation. We study how the magnetic field of a series of ARs evolves with time to better…

Deep convolutional neural networks (CNNs) have achieved breakthrough performance in many pattern recognition tasks such as image classification. However, the development of high-quality deep models typically relies on a substantial amount…

Deep convolutional neural networks (CNNs) are appealing for the purpose of classification of hand movements from surface electromyography (sEMG) data because they have the ability to perform automated person-specific feature extraction from…

Current brain surface-based prediction models often overlook the variability of regional attributes at the cortical feature level. While graph neural networks (GNNs) excel at capturing regional differences, they encounter challenges when…

Aims. Moreno-Insertis et al. (2018) recently discovered two types of flux emergence in their numerical simulations: magnetic loops and magnetic sheet emergence. Whereas magnetic loop emergence has been documented well in the last years, by…

We introduce an approach for analyzing the variation of features generated by convolutional neural networks (CNNs) with respect to scene factors that occur in natural images. Such factors may include object style, 3D viewpoint, color, and…

We present results from 3D magnetohydrodynamic (MHD) simulations of the emergence of a twisted convection zone flux tube into a pre-existing coronal dipole field. As in previous simulations, following the partial emergence of the…

Solar flares are among the most powerful and dynamic events in the solar system, resulting from the sudden release of magnetic energy stored in the Sun's atmosphere. These energetic bursts of electromagnetic radiation can release up to…

The sudden release of magnetic energy on the Sun drives powerful solar flares and coronal mass ejections. The key issue is the difficulty in predicting the occurrence time and location of strong solar eruptions, i.e., those leading to the…

Magnetic field data provided by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory were utilized to explore the changes in the magnetic energy of four active regions (ARs) during their emergence. We found that at…

Deep learning models have provided huge interpretation power for image-like data. Specifically, convolutional neural networks (CNNs) have demonstrated incredible acuity for tasks such as feature extraction or parameter estimation. Here we…

Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high energy physics. In this paper, we attempt to understand the potential of CNNs for event…

Nowadays, deep learning can be employed to a wide ranges of fields including medicine, engineering, etc. In deep learning, Convolutional Neural Network (CNN) is extensively used in the pattern and sequence recognition, video analysis,…

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 $\ge M$,…

The ability to automatically detect certain types of cells or cellular subunits in microscopy images is of significant interest to a wide range of biomedical research and clinical practices. Cell detection methods have evolved from…

Convolutional neural networks (CNNs) have become widely adopted in gravitational wave (GW) detection pipelines due to their ability to automatically learn hierarchical features from raw strain data. However, the physical meaning of these…

Porous media is widely distributed in nature, found in environments such as soil, rock formations, and plant tissues, and is crucial in applications like subsurface oil and gas extraction, medical drug delivery, and filtration systems.…

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…

Deep Convolutional Neural Network (CNN) is a special type of Neural Networks, which has shown exemplary performance on several competitions related to Computer Vision and Image Processing. Some of the exciting application areas of CNN…