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  • 2012.01301v1

    Submitted manuscript, 4.49 MB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License


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Cosmic Background Removal with Deep Neural Networks in SBND

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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


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.