相关论文: Performance of solar far-side active regions neura…
The detection of earthquakes is a fundamental prerequisite for seismology and contributes to various research areas, such as forecasting earthquakes and understanding the crust/mantle structure. Recent advances in machine learning…
A new approach to seismic interpretation is proposed to leverage visual perception and human visual system modeling. Specifically, a saliency detection algorithm based on a novel attention model is proposed for identifying subsurface…
We analyse the topology of photospheric magnetic fields and sub-photospheric flows of several active regions (ARs) that are observed during the peak to descending phase of the solar cycle 23. Our analysis shows clear evidence of hemispheric…
The heliospheric magnetic field (HMF) is structured into large sectors of positive and negative polarity. The parts of the boundary between these sectors where the change in polarity matches that of the leading-to-following sunspot polarity…
Efficient prediction of solar flares relies on parameters that quantify the eruptive capability of solar active regions. Several such quantitative predictors have been proposed in the literature, inferred mostly from photospheric…
The spatial distribution of energetic protons contributes towards the understanding of magnetospheric dynamics. Based upon 17 years of the Cluster/RAPID observations, we have derived machine learning-based models to predict the proton…
A deep neural network (NN) is used to simultaneously detect laser beams in images and measure their center coordinates, radii and angular orientations. A dataset of images containing simulated laser beams and a dataset of images with…
Stellar activity is a potential important limitation to the detection of low mass extrasolar planets with indirect methods (RV, photometry, astrometry). In previous papers, using the Sun as a proxy, we investigated the impact of stellar…
Accurate and reliable predictions of solar flares are essential due to their potentially significant impact on Earth and space-based infrastructure. Although deep learning models have shown notable predictive capabilities in this domain,…
The solar atmosphere is extremely dynamic, and many important phenomena develop on small scales that are unresolved in observations with the Helioseismic and Magnetic Imager (HMI) instrument on the Solar Dynamics Observatory (SDO). For…
We continue our attempt to connect observational data on current helicity in solar active regions with solar dynamo models. In addition to our previous results about temporal and latitudinal distributions of current helicity (Kleeorin et…
While supervised neural networks have become state of the art for identifying the rare strong gravitational lenses from large imaging data sets, their selection remains significantly affected by the large number and diversity of nonlens…
Monitoring remote forests is a global challenge central to climate mitigation and biodiversity conservation, yet satellite observations are frequently limited by weather, dense canopies, and solar dependency. Here we show that passive…
Recognizing seismic waves immediately is very important for the realization of efficient disaster prevention. Generally these systems consist of a network of seismic detectors that send real time data to a central server. The server…
In this dataset we provide a comprehensive collection of magnetograms (images quantifying the strength of the magnetic field) from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO). The dataset…
A procedure is introduced to recognise sunspots automatically in solar full-disk photosphere images obtained from Huairou Solar Observing Station, National Astronomical Observatories of China. The images are first pre-processed through…
The extensive ubiquitous availability of sensors in smart devices and the Internet of Things (IoT) has opened up the possibilities for implementing sensor-based activity recognition. As opposed to traditional sensor time-series processing…
Thanks to their high quality, new and upcoming asteroseismic observations - with CoRoT, Kepler, and from the ground... - can benefit from the experience gained with helioseismology. We focus in this paper on solar-like oscillations, for…
In image denoising problems, the increasing density of available images makes an exhaustive visual inspection impossible and therefore automated methods based on machine-learning must be deployed for this purpose. This is particulary the…
Knowing the behavior of solar radiation at a geographic location is essential for the use of energy from the sun using photovoltaic systems; however, the number of stations for measuring meteorological parameters and for determining the…