Related papers: Deep learning with photosensor timing information …
The application of deep learning techniques using convolutional neural networks to the classification of particle collisions in High Energy Physics is explored. An intuitive approach to transform physical variables, like momenta of…
Water Cherenkov detectors offer a robust and economical solution for real-time radiation monitoring by detecting Cherenkov light from charged particles moving faster than light in water. This work presents a novel two-stage classification…
A 3-day international workshop on atmospheric monitoring and calibration for high-energy astroparticle detectors, with a view towards next-generation facilities. The atmosphere is an integral component of many high-energy astroparticle…
The last 20 years have seen the development of new techniques in Astroparticle Physics providing access to the highest end of the electromagnetic spectrum. It has been shown that some sources emit photons up to energies close to 100 TeV.…
In this paper two new learning-based eXplainable AI (XAI) methods for deep convolutional neural network (DCNN) image classifiers, called L-CAM-Fm and L-CAM-Img, are proposed. Both methods use an attention mechanism that is inserted in the…
The upcoming Cherenkov Telescope Array (CTA) project is expected to provide unprecedented sensitivity in the low-energy ( <~100 GeV) range for Cherenkov telescopes. In order to exploit fully the potential of the telescopes the standard…
In the present paper, we propose a source camera identification method for mobile devices based on deep learning. Recently, convolutional neural networks (CNNs) have shown a remarkable performance on several tasks such as image recognition,…
Several types of binary systems have been detected up to now at high and very high gamma-ray energies, including microquasars, young pulsars around massive stars and colliding wind binaries. The study of the sources already known, and of…
Gamma-ray astronomy from hundreds of GeV to PeV is confined to ground-based experiments that detect air showers induced by $\gamma$-rays entering Earth's atmosphere. While particle detector arrays feature huge detection areas, accurately…
Even though convolutional neural networks can classify objects in images very accurately, it is well known that the attention of the network may not always be on the semantically important regions of the scene. It has been observed that…
In photo-sensor cameras of Cherenkov telescopes the light images from particle showers always contain the background noise induced by photons of the night sky. An image cleaning procedure is needed to reduce the contribution of those noise…
For air showers observed simultaneously by more than two imaging atmospheric Cherenkov telescopes, the shower geometry is overconstrained by the images and image information should be combined taking into account the quality of the images.…
Imaging Air Cherenkov Telescopes (IACTs) detect the Cherenkov light flashes of Extended Air Showers (EAS) triggered by very high energy (VHE) gamma-rays impinging on the Earth's atmosphere. Due to the overwhelming background from hadron…
A peculiar aspect of Cherenkov telescopes is that they are designed to detect atmospheric light flashes on the time scale of nanoseconds, being almost blind to stellar sources. As a consequence, the pointing calibration of these instruments…
The site selection group for the future Cherenkov Telescope Array (CTA) has deployed sensitive light sensors at 9 candidate sites, 5 of them in the Southern and 4 in the Northern hemisphere. The sensors are equipped with a PIN diode and a…
Imaging Atmospheric Cherenkov Telescopes (IACTs) have resulted in a breakthrough in very-high energy (VHE) gamma-ray astrophysics. While early IACT installations faced the problem of detecting any sources at all, current instruments are…
Understanding transformations under electron beam irradiation requires mapping the structural phases and their evolution in real time. To date, this has mostly been a manual endeavor comprising of difficult frame-by-frame analysis that is…
This study applied representation learning algorithms to satellite images and evaluated the learned latent spaces with classifications of various weather events. The algorithms investigated include the classical linear transformation, i.e.,…
The Cherenkov Telescope Array (CTA) will be the next generation instrument for the very high energy gamma-ray astrophysics domain. With its enhanced sensitivity in comparison with the current facilities, CTA is expected to shed light on a…
The ability to discover new transients via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine Learning techniques such as…