40 citations · 72 across the 9 of their papers we have counts for
4 papers · 1 filter
Exploring the Potential of the Pulsed Laser onboard the CALIPSO Satellite to Improve Calibration with VERITAS
Gregory Foote
Imaging Atmospheric Cherenkov Telescopes (IACTs) are used to detect bright nanosecond-duration flashes of optical light originating from interactions of cosmic/gamma-rays in the at…
Studying deep convolutional neural networks with hexagonal lattices for imaging atmospheric Cherenkov telescope event reconstruction
D. Nieto, A. Brill, Q. Feng +4
Deep convolutional neural networks (DCNs) are a promising machine learning technique to reconstruct events recorded by imaging atmospheric Cherenkov telescopes (IACTs), but require…
Muon Hunter: a Zooniverse project
R. Bird, M. K. Daniel, H. Dickinson +8
The large datasets and often low signal-to-noise inherent to the raw data of modern astroparticle experiments calls out for increasingly sophisticated event classification techniqu…
A citizen-science approach to muon events in imaging atmospheric Cherenkov telescope data: the Muon Hunter
Q. Feng, J. Jarvis
Event classification is a common task in gamma-ray astrophysics. It can be treated with rapidly-advancing machine learning algorithms, which have the potential to outperform tradit…