Related papers: Cosmic Ray Rejection with Attention Augmented Deep…
An observation-based Galactic Cosmic Ray (GCR) spectral model for heavy nuclei is developed. Zhao and Qin (J. Geophys. Res. Space Phys.118, 1837(2013)) proposed an empirical elemental GCR spectra model for nuclear charge 5-28 over the…
Cosmic rays (CRs) are protons and atomic nuclei that flow into our Solar system and reach the Earth with energies of up to ~10^21 eV. The sources of ultra-high energy cosmic rays (UHECRs) with E >~ 10^19 eV remain unknown, although there…
The extremely low flux of ultra-high energy cosmic rays (UHECR) makes their direct observation by orbital experiments practically impossible. For this reason all current and planned UHECR experiments detect cosmic rays indirectly by…
Cosmic ray (CR) physics has entered a precision-driven era. With the latest AMS-02 nuclei data (boron-to-carbon ratio, proton flux, helium flux and antiproton-to-proton ratio), we perform a global fitting and constrain the primary source…
Wide field small aperture telescopes are widely used for optical transient observations. Detection and classification of astronomical targets in observed images are the most important and basic step. In this paper, we propose an…
Cosmic rays are the most outstanding example of accelerated particles. They are about 1\% of the total mass of the Universe, so that cosmic rays would represent by far the most important energy transformation process of the Universe.…
Anomaly Detection involves identifying deviations from normal data distributions and is critical in fields such as medical diagnostics and industrial defect detection. Traditional AD methods typically require the availability of normal…
X-ray observations of galaxy clusters are impacted by the presence of active galactic nuclei (AGNs) in a manner that is challenging to quantify, leading to biases in the detection and measurement of cluster properties for both astrophysics…
This paper presents a novel keypoints-based attention mechanism for visual recognition in still images. Deep Convolutional Neural Networks (CNNs) for recognizing images with distinctive classes have shown great success, but their…
Cosmic-ray (CR) antihelium is an important observable for dark matter (DM) indirect searches due to extremely low secondary backgrounds towards low energies. In a given DM model, the predicted CR antihelium flux is expected to be strongly…
The presence of cloud layers severely compromises the quality and effectiveness of optical remote sensing (RS) images. However, existing deep-learning (DL)-based Cloud Removal (CR) techniques encounter difficulties in accurately…
To maximise data output from single-shot astronomical images, the rejection of cosmic rays is important. We present the results of a benchmark trial comparing various cosmic ray rejection algorithms. The procedures assess relative…
Diabetic retinopathy (DR) is a leading cause of preventable blindness, and automated fundus image grading can play an important role in large-scale screening. In this work, we investigate three CLIP-based approaches for five-class DR…
The Fermilab Short Baseline Neutrino (SBN) program aims to observe and reconstruct thousands of neutrino-argon interactions with its three detectors (SBND, MicroBooNE and ICARUS-T600), using their hundred of tonnes Liquid Argon Time…
Impact craters are formed as a result of continuous impacts on the surface of planetary bodies. This paper proposes a novel way of simultaneously utilizing optical images, digital elevation maps (DEMs), and slope maps for automatic crater…
Recent years have seen many arguments for cosmic rays (CRs) as an important influence on galactic and circumgalactic (CGM) physics, star and galaxy formation. We present a pedagogical overview of state-of-the-art modeling of…
The Cosmic Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic ray ensembles (CRE): groups of a minimum of two CR with a common primary…
We present a deep learning method for accurately localizing the center of a single corneal reflection (CR) in an eye image. Unlike previous approaches, we use a convolutional neural network (CNN) that was trained solely using simulated…
Purpose: To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs; secondary aim to explore potential utility in detecting central GA (CGA). Design: A deep learning model was developed…
Deep field observations are an essential tool to probe the cosmological evolution of galaxies. In this context, X-ray deep fields provide information about some of the most energetic cosmological objects: active galactic nuclei (AGN).…