Identifying Tracks Duplicates via Neural Network

The goal of the project is to study feasibility of state of the art machine learning techniques in track reconstruction. Machine learning techniques provide promising ways to speed up the pattern recognition of tracks by adding more intelligence in the algorithms. Implementation of neural network to...

Descripción completa

Detalles Bibliográficos
Autores principales: Sunjerga, Antonio, Kortelainen, Matti
Lenguaje:eng
Publicado: 2017
Materias:
Computing and Computers
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2280213
_version_ 1780955522316369920
author Sunjerga, Antonio
Kortelainen, Matti
author_facet Sunjerga, Antonio
Kortelainen, Matti
author_sort Sunjerga, Antonio
collection CERN
description The goal of the project is to study feasibility of state of the art machine learning techniques in track reconstruction. Machine learning techniques provide promising ways to speed up the pattern recognition of tracks by adding more intelligence in the algorithms. Implementation of neural network to process of track duplicates identifying will be discussed. Different approaches are shown and results are compared to method that is currently in use.
id cern-2280213
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2017
record_format invenio
spelling cern-22802132019-09-30T06:29:59Zhttp://cds.cern.ch/record/2280213engSunjerga, AntonioKortelainen, MattiIdentifying Tracks Duplicates via Neural NetworkComputing and ComputersParticle Physics - ExperimentThe goal of the project is to study feasibility of state of the art machine learning techniques in track reconstruction. Machine learning techniques provide promising ways to speed up the pattern recognition of tracks by adding more intelligence in the algorithms. Implementation of neural network to process of track duplicates identifying will be discussed. Different approaches are shown and results are compared to method that is currently in use.CERN-STUDENTS-Note-2017-090oai:cds.cern.ch:22802132017-08-18
spellingShingle Computing and Computers
Particle Physics - Experiment
Sunjerga, Antonio
Kortelainen, Matti
Identifying Tracks Duplicates via Neural Network
title Identifying Tracks Duplicates via Neural Network
title_full Identifying Tracks Duplicates via Neural Network
title_fullStr Identifying Tracks Duplicates via Neural Network
title_full_unstemmed Identifying Tracks Duplicates via Neural Network
title_short Identifying Tracks Duplicates via Neural Network
title_sort identifying tracks duplicates via neural network
topic Computing and Computers
Particle Physics - Experiment
url http://cds.cern.ch/record/2280213
work_keys_str_mv AT sunjergaantonio identifyingtracksduplicatesvianeuralnetwork
AT kortelainenmatti identifyingtracksduplicatesvianeuralnetwork

Ejemplares similares