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Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing

Detalles Bibliográficos
Autores principales: Moons, Bert, Bankman, Daniel, Verhelst, Marian
Lenguaje:eng
Publicado: Springer 2019
Materias:
Acceso en línea:http://cds.cern.ch/record/2665188
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author Moons, Bert
Bankman, Daniel
Verhelst, Marian
author_facet Moons, Bert
Bankman, Daniel
Verhelst, Marian
author_sort Moons, Bert
collection CERN
id cern-2665188
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
publisher Springer
record_format invenio
spelling cern-26651882021-04-21T18:28:20Zhttp://cds.cern.ch/record/2665188engMoons, BertBankman, DanielVerhelst, MarianEmbedded deep learning: algorithms, architectures and circuits for always-on neural network processingComputing and ComputersSpringeroai:cds.cern.ch:26651882019
spellingShingle Computing and Computers
Moons, Bert
Bankman, Daniel
Verhelst, Marian
Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
title Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
title_full Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
title_fullStr Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
title_full_unstemmed Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
title_short Embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
title_sort embedded deep learning: algorithms, architectures and circuits for always-on neural network processing
topic Computing and Computers
url http://cds.cern.ch/record/2665188
work_keys_str_mv AT moonsbert embeddeddeeplearningalgorithmsarchitecturesandcircuitsforalwaysonneuralnetworkprocessing
AT bankmandaniel embeddeddeeplearningalgorithmsarchitecturesandcircuitsforalwaysonneuralnetworkprocessing
AT verhelstmarian embeddeddeeplearningalgorithmsarchitecturesandcircuitsforalwaysonneuralnetworkprocessing