Automatic Design of Artificial Neural Networks for Gamma-Ray Detection
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Aug 8, 2019 · The goal of this work is to investigate the possibility of improving current gamma/hadron discrimination based on the shower patterns recorded on the ground.
May 9, 2019 · These results show that it is possible to improve the gamma/hadron discrimination based on CNNs that are automatically generated and are trained ...
These results establish a new state-of-the-art in the gamma/hadron discrimination problem, based on the ground impact patterns, and prove that CNNs ...
To this end, we propose the use of Convolutional Neural Networks (CNNs) for their ability to distinguish patterns based on automatically designed features.
Jul 15, 2019 · ABSTRACT The goal of this work is to investigate the possibility of improving current gamma/hadron discrimination based on the shower ...
To this end, we propose the use of Convolutional Neural Networks (CNNs) for their ability to distinguish patterns based on automatically designed features.
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This work will focus on comparing the performance of a fully-connected NN and a CNN for automated gamma-ray spectroscopy.
Jun 20, 2023 · In this work, we use a neural network model trained on synthetic NaI(Tl) urban search data to compare some of these explanation methods and identify ...