Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs

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Slides for ICNFP 2021

Detalles Bibliográficos
Autor principal: Fortin, Etienne Marie
Lenguaje:eng
Publicado: 2021
Materias:
Particle Physics - Experiment
Acceso en línea:http://cds.cern.ch/record/2779611
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author Fortin, Etienne Marie
author_facet Fortin, Etienne Marie
author_sort Fortin, Etienne Marie
collection CERN
description Slides for ICNFP 2021
id cern-2779611
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2021
record_format invenio
spelling cern-27796112021-08-31T22:20:50Zhttp://cds.cern.ch/record/2779611engFortin, Etienne MarieMachine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAsParticle Physics - ExperimentSlides for ICNFP 2021ATL-LARG-SLIDE-2021-457oai:cds.cern.ch:27796112021-08-31
spellingShingle Particle Physics - Experiment
Fortin, Etienne Marie
Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
title Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
title_full Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
title_fullStr Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
title_full_unstemmed Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
title_short Machine Learning for Real-Time Processing of ATLAS Liquid Argon Calorimeter Signals with FPGAs
title_sort machine learning for real-time processing of atlas liquid argon calorimeter signals with fpgas
topic Particle Physics - Experiment
url http://cds.cern.ch/record/2779611
work_keys_str_mv AT fortinetiennemarie machinelearningforrealtimeprocessingofatlasliquidargoncalorimetersignalswithfpgas

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