Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Convolutional Neural Network Neutrino Event Classifier   Convolutional neural networks (CNNs) have been widely applied in the computer
vision community to solve complex problems in image recognition and analysis.
We describe an application of the CNN technology to the problem of identifying
particle interactions in sampling calorimeters used commonly in high energy
physics and high energy neutrino physics in particular. Following a discussion
of the core concepts of CNNs and recent innovations in CNN architectures
related to the field of deep learning, we outline a specific application to the
NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network)
identifies neutrino interactions based on their topology without the need for
detailed reconstruction and outperforms algorithms currently in use by the NOvA
collaboration.

15
The categories of this paper are: nucl-ex
37
The categories of this paper are: supr-con
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
10
The categories of this paper are: q-bio
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
17
The categories of this paper are: q-fin
26
The categories of this paper are: bayes-an