Multi-View Deep Learning for Imaging Atmospheric Cherenkov Telescopes

Autor:	Warnhofer, Hannes, Spencer, Samuel T., Mitchell, Alison M. W.
Rok vydání:	2024
Předmět:	Astrophysics - Instrumentation and Methods for Astrophysics Astrophysics - High Energy Astrophysical Phenomena
Zdroj:	2024 Res. Notes AAS 8 91
Druh dokumentu:	Working Paper
DOI:	10.3847/2515-5172/ad382a
Popis:	This research note concerns the application of deep-learning-based multi-view-imaging techniques to data from the H.E.S.S. Imaging Atmospheric Cherenkov Telescope array. We find that the earlier the fusion of layer information from different views takes place in the neural network, the better our model performs with this data. Our analysis shows that the point in the network where the information from the different views is combined is far more important for the model performance than the method used to combine the information. Comment: Accepted in Research Notes of the American Astronomical Society. 3 Pages, 1 Figure
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2403.18516 Zobrazit plný text záznamu View this record from Arxiv