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  • 2012.01301v1

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Cosmic Background Removal with Deep Neural Networks in SBND

Research output: Contribution to journalJournal articlepeer-review

Published
Article number649917
<mark>Journal publication date</mark>24/08/2021
<mark>Journal</mark>Frontiers in Artificial Intelligence
Volume4
Number of pages14
Publication StatusPublished
<mark>Original language</mark>English

Abstract

In this paper, we have demonstrated a novel technique for pixel level segmentation to remove cosmic backgrounds from LArTPC images. We have shown how different deep neural networks can be designed and trained for this task, and presented metrics that can be used to select the best versions. The technique developed is applicable to other LArTPC detectors running at surface level, such as MicroBooNE, ICARUS and ProtoDUNE. We anticipate future publications studying the hyperparameters of these networks, and an updated dataset with a more realistic detector simulation prior to the application of this technique to real neutrino data.