7 citations · 11 across the 3 of their papers we have counts for
3 papers
Image Data Augmentation for the TAIGA-IACT Experiment with Conditional Generative Adversarial Networks
Yu. Yu. Dubenskaya, A. P. Kryukov, E. O. Gres +5
Modern Imaging Atmospheric Cherenkov Telescopes (IACTs) generate a huge amount of data that must be classified automatically, ideally in real time. Currently, machine learning-base…
Gamma/hadron separation in the TAIGA experiment with neural network methods
E. O. Gres, A. P. Kryukov, P. A. Volchugov +5
In this work, the ability of rare VHE gamma ray selection with neural network methods is investigated in the case when cosmic radiation flux strongly prevails (ratio up to {10^4} o…
Using a Conditional Generative Adversarial Network to Control the Statistical Characteristics of Generated Images for IACT Data Analysis
Julia Dubenskaya, Alexander Kryukov, Andrey Demichev +3
Generative adversarial networks are a promising tool for image generation in the astronomy domain. Of particular interest are conditional generative adversarial networks (cGANs), w…