Scalable, End-to-End, Deep-Learning-Based Data Reconstruction Chain for Particle Imaging Detectors

Recent inroads in Computer Vision (CV) and Machine Learning (ML) have motivated a new approach to the analysis of particle imaging detector data. Unlike previous efforts which tackled isolated CV tasks, this paper introduces an end-to-end, ML-based data reconstruction chain for Liquid Argon Time Pro...

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Veröffentlicht in:	arXiv.org 2021-02
Hauptverfasser:	Drielsma, Francois, Terao, Kazuhiro, Dominé, Laura, Dae Heun Koh
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Argon Artificial neural networks Chains Computer vision Deep learning Feature extraction Image reconstruction Machine learning Neural networks Neutrinos Physics Superstructures
Online-Zugang:	Volltext
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