@article{cc34e911458b47a1b54306ee8f481098,
title = "Deep neural network for pixel-level electromagnetic particle identification in the MicroBooNE liquid argon time projection chamber",
abstract = "We have developed a convolutional neural network that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. The goal of this work is to develop a complete deep neural network based data reconstruction chain for the MicroBooNE detector. We show the first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images. The demonstration is performed for stopping muon and a νμ charged-current neutral pion data samples.",
author = "{MicroBooNE collaboration} and C. Adams and M. Alrashed and R. An and J. Anthony and J. Asaadi and A. Ashkenazi and M. Auger and S. Balasubramanian and B. Baller and C. Barnes and G. Barr and M. Bass and F. Bay and A. Bhat and K. Bhattacharya and M. Bishai and A. Blake and T. Bolton and L. Camilleri and D. Caratelli and {Caro Terrazas}, I. and R. Carr and {Castillo Fernandez}, R. and F. Cavanna and G. Cerati and Y. Chen and E. Church and D. Cianci and Cohen, {E. O.} and Collin, {G. H.} and Conrad, {J. M.} and M. Convery and L. Cooper-Troendle and Crespo-Anad{\'o}n, {J. I.} and {Del Tutto}, M. and D. Devitt and A. Diaz and Evans, {J. J.} and Furmanski, {A. P.} and D. Garcia-Gamez and O. Goodwin and P. Guzowski and J. Hewes and C. Hill and L. Jiang and G. Karagiorgi and K. Mistry and R. Murrells and A. Smith and Szelc, {A. M.}",
year = "2019",
month = may,
doi = "10.1103/PhysRevD.99.092001",
language = "English",
volume = "99",
journal = "Physical Review D",
issn = "2470-0010",
publisher = "American Physical Society",
number = "9",
}