Related papers: Deep learning detection of transients (ICRC-2019)
Imaging Air Cherenkov Telescopes (IACTs) are essential to ground-based observations of gamma rays in the GeV to TeV regime. One particular challenge of ground-based gamma-ray astronomy is an effective rejection of the hadronic background.…
Noise of non-astrophysical origin will contaminate science data taken by the Advanced Laser Interferometer Gravitational-wave Observatory (aLIGO) and Advanced Virgo gravitational-wave detectors. Prompt characterization of instrumental and…
There are several networks of precision quantum sensors in existence, including networks of atomic clocks, magnetometers, and gravitational wave detectors. These networks can be re-purposed for searches of exotic physics, such as direct…
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…
Due to the limited field of view (FoV) of Cherenkov telescopes, the time needed to achieve target sensitivity for surveys of the extragalactic and Galactic sky is large. To optimize the time spent to perform such surveys, a so-called…
Robotic wide-field time-domain surveys, such as the Zwicky Transient Facility and the Asteroid Terrestrial-impact Last Alert System, capture dozens of transients each night. The workflows for discovering and classifying transients in survey…
The ability to quickly detect transient sources in optical images and trigger multi-wavelength follow up is key for the discovery of fast transients. These include events rare and difficult to detect such as kilonovae, supernova shock…
We propose a dedicated analysis approach for indirect Dark Matter searches with Imaging Air Cherenkov Telescopes. By using the full likelihood analysis, we take complete advantage of the distinct features expected in the gamma ray spectrum…
We discuss the prospects for the detection of gamma-ray bursts (GRBs) by the Cherenkov Telescope Array (CTA), the next generation, ground-based facility of imaging atmospheric Cherenkov telescopes (IACTs) operating above a few tens of GeV.…
Searches for counterparts to multimessenger events with optical imagers use difference imaging to detect new transient sources. However, even with existing artifact detection algorithms, this process simultaneously returns several classes…
Exploration of the transient Universe is an exciting and fast-emerging area within radio astronomy. Known transient phenomena range in time scales from sub-nanoseconds to years or longer, thus spanning a huge range in time domain and…
We outline the science prospects for gamma-ray bursts (GRBs) with the Cherenkov Telescope Array (CTA), the next-generation ground-based gamma-ray observatory operating at energies above few tens of GeV. With its low energy threshold, large…
In this paper, we propose a fast deep learning method for object saliency detection using convolutional neural networks. In our approach, we use a gradient descent method to iteratively modify the input images based on the pixel-wise…
A Bayesian approach is presented for detecting and characterising the signal from discrete objects embedded in a diffuse background. The approach centres around the evaluation of the posterior distribution for the parameters of the discrete…
Ground-based gamma-ray astronomy has experienced a major breakthrough in the last decade thanks to the advent of new generation instruments such as H.E.S.S., MAGIC, Milagro and VERITAS. A large variety of cosmic particle accelerators has…
Anomaly detection in surveillance videos has been recently gaining attention. A challenging aspect of high-dimensional applications such as video surveillance is continual learning. While current state-of-the-art deep learning approaches…
When very-high-energy gamma rays interact high in the Earth's atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into…
The sensitivity of astronomical X-ray detectors is limited by the instrumental background. The background is especially important when observing low surface brightness sources that are critical for many of the science cases targeted by…
This paper presents an novel object type classification method for automotive applications which uses deep learning with radar reflections. The method provides object class information such as pedestrian, cyclist, car, or non-obstacle. The…
The recent discovery of electromagnetic signals in coincidence with neutron-star mergers has solidified the importance of multimessenger campaigns in studying the most energetic astrophysical events. Pioneering multimessenger observatories,…