Cosmic Background Removal with Deep Neural Networks in SBND

, SBND Collaboration and Brailsford, D. and Nowak, Jaroslaw and Lay, Henry (2021) Cosmic Background Removal with Deep Neural Networks in SBND. Frontiers in Artificial Intelligence, 4. ISSN 2624-8212

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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.

Item Type:
Journal Article
Journal or Publication Title:
Frontiers in Artificial Intelligence
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2610
Subjects:
ID Code:
159082
Deposited By:
Deposited On:
01 Sep 2021 14:10
Refereed?:
Yes
Published?:
Published
Last Modified:
17 Oct 2021 05:34