Related papers: Automatic detection of CMEs using synthetically-tr…
Context. We study two coronal mass ejections (CMEs) observed between April 1-2, 2019 by both the inner Wide-Field Imager for Parker Solar Probe (WISPR-I) and the inner heliospheric imager (HI-1) on board STEREO-A. This is the first study of…
This paper proposes a novel automatically generating image masks method for the state-of-the-art Mask R-CNN deep learning method. The Mask R-CNN method achieves the best results in object detection until now, however, it is very…
Forecasting the in situ properties of coronal mass ejections (CMEs) from remote images is expected to strongly enhance predictions of space weather, and is of general interest for studying the interaction of CMEs with planetary…
Since Coronal Mass Ejections (CMEs) are the major drivers of space weather, it is crucial to study their evolution starting from the inner corona. In this work we use Graduated Cylindrical Shell (GCS) model to study the 3D evolution of 59…
In a case study (June 6-7, 2008) we report on how the internal structure of a coronal mass ejection (CME) at 1 AU can be anticipated from remote observations of white-light images of the heliosphere. Favorable circumstances are the absence…
Coronal mass ejections (CMEs) are large-scale ejections of magnetized plasma from the Sun and are associated with the most extreme space weather events. The geoeffectiveness of a CME is primarily determined by the southward component of its…
Coronal mass ejections (CMEs) are the most geoeffective space weather phenomena, being associated with large geomagnetic storms, having the potential to cause disturbances to telecommunication, satellite network disruptions, power grid…
Alerts of potentially hazardous coronal mass ejections (CME) are based on the detection of rapid changes in remote observations of the solar atmosphere. This paper presents a method that detects and estimates the central coordinates of CME…
Context. Observations reveal that shocks can be driven by fast coronal mass ejections (CMEs) and play essential roles in particle accelerations. A critical ratio, $\delta$, derived from a shock standoff distance normalized by the radius of…
This study addresses the limitations of single-viewpoint observations of Coronal Mass Ejections (CMEs) by presenting results from a 3D catalog of 360 CMEs during solar cycle 24, fitted using the GCS model. The dataset combines 326…
A method for the full three-dimensional (3-D) reconstruction of the trajectories of coronal mass ejections (CMEs) using Solar TErrestrial RElations Observatory (STEREO) data is presented. Four CMEs that were simultaneously observed by the…
The Solar TErrestrial RElations Observatory (STEREO) provides high cadence and high resolution images of the structure and morphology of coronal mass ejections (CMEs) in the inner heliosphere. CME directions and propagation speeds have…
The complex background in the soil image collected in the field natural environment will affect the subsequent soil image recognition based on machine vision. Segmenting the soil center area from the soil image can eliminate the influence…
Coronal mass ejections (CMEs) are the main driver of Space Weather. Therefore, a precise forecasting of their likely geo-effectiveness relies on an accurate tracking of their morphological and kinematical evolution throughout the…
Coronal mass ejections (CMEs) are among the most energetic phenomena in our solar system, with significant implications for space weather. Understanding their early dynamics remains challenging due to observational limitations in the low…
Solar Coronal mass ejections (CMEs) are large-scale ejections of plasma and magnetic field from the corona, which propagate through interplanetary space. CMEs are the most significant drivers of adverse space weather on Earth, but the…
Coronal mass ejections (CMEs) are solar eruptions of plasma and magnetic fields that significantly impact Space Weather, causing disruptions in technological systems and potential damage to power grids when directed towards Earth.…
Despite the recent advances of deep learning algorithms in medical imaging, the automatic segmentation algorithms for kidneys in MRI exams are still scarce. Automated segmentation of kidneys in Magnetic Resonance Imaging (MRI) exams are…
Electrocardiogram (ECG) analysis is a fundamental tool for diagnosing cardiovascular conditions, yet anomaly detection in ECG signals remains challenging due to their inherent complexity and variability. We propose Multi-scale Masked…
We present a new method to extract the three-dimensional electron density profile and density compression ratio of shock fronts associated with Coronal Mass Ejections (CMEs) observed in white light coronagraph images. We demonstrate the…