most citedDeep Learning for Energy Estimation and Particle Identification in Gamma-ray Astronomy

13 citations · 13 across the 1 of their papers we have counts for

collaborators

8 papers

astro-ph.IM2019

Quest for detection of a cosmological signal from neutral hydrogen with a digital radio array developed for air-shower measurements

D. Kostunin, P. Bezyazeekov, N. Budnev +12

Digital radio arrays are widely used for the low-frequency radio astronomy as well as for detection of air-showers induced by high-energy cosmic rays and neutrinos. Since the radio…

astro-ph.IM2019

German-Russian Astroparticle Data Life Cycle Initiative

Andreas Haungs, Igor Bychkov, Julia Dubenskaya +19

A data life cycle (DLC) is a high-level data processing pipeline that involves data acquisition, event reconstruction, data analysis, publication, archiving, and sharing. For astro…

astro-ph.IM201913 cited

Deep Learning for Energy Estimation and Particle Identification in Gamma-ray Astronomy

Evgeny Postnikov, Alexander Kryukov, Stanislav Polyakov +1

Deep learning techniques, namely convolutional neural networks (CNN), have previously been adapted to select gamma-ray events in the TAIGA experiment, having achieved a good qualit…

astro-ph.IM2018

A distributed data warehouse system for astroparticle physics

Minh-Duc Nguyen, Alexander Kryukov, Julia Dubenskaya +10

A distributed data warehouse system is one of the actual issues in the field of astroparticle physics. Famous experiments, such as TAIGA, KASCADE-Grande, produce tens of terabytes…

astro-ph.IM2018

Particle identification in ground-based gamma-ray astronomy using convolutional neural networks

E. B. Postnikov, I. V. Bychkov, J. Y. Dubenskaya +10

Modern detectors of cosmic gamma-rays are a special type of imaging telescopes (air Cherenkov telescopes) supplied with cameras with a relatively large number of photomultiplier-ba…

astro-ph.IM2018

Using Binary File Format Description Languages for Documenting, Parsing, and Verifying Raw Data in TAIGA Experiment

I. Bychkov, A. Demichev, J. Dubenskaya +13

The paper is devoted to the issues of raw binary data documenting, parsing and verifying in astroparticle data lifecycle. The long-term preservation of raw data of astroparticle ex…