An optimized convolutional neural network for arrhythmia classification

An optimized convolutional neural network for arrhythmia classification by Shan, Wei Chen

Détails bibliographiques
Auteur principal: Shan, Wei Chen
Format: thesis
Langue:malais
Publié: Tanjong Malim 2022
Sujets:
Accès en ligne:https://ir.upsi.edu.my/detailsg.php?det=9598
Abstract Abstract here
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author Shan, Wei Chen
author_facet Shan, Wei Chen
author_sort Shan, Wei Chen
description An optimized convolutional neural network for arrhythmia classification by Shan, Wei Chen
format thesis
id oai:ir.upsi.edu.my:9598
institution Universiti Pendidikan Sultan Idris
language zsm
publishDate 2022
publisher Tanjong Malim
record_format eprints
record_pdf Abstract
spelling oai:ir.upsi.edu.my:95982023-10-20 https://ir.upsi.edu.my/detailsg.php?det=9598 An optimized convolutional neural network for arrhythmia classification Shan, Wei Chen Q Science Tanjong Malim Fakulti Seni, Komputeran dan Industri Kreatif 2022 thesis text zsm N/A https://ir.upsi.edu.my/detailsg.php?det=9598 openAccess An optimized convolutional neural network for arrhythmia classification by Shan, Wei Chen
spellingShingle Q Science
Shan, Wei Chen
An optimized convolutional neural network for arrhythmia classification
title An optimized convolutional neural network for arrhythmia classification
title_full An optimized convolutional neural network for arrhythmia classification
title_fullStr An optimized convolutional neural network for arrhythmia classification
title_full_unstemmed An optimized convolutional neural network for arrhythmia classification
title_short An optimized convolutional neural network for arrhythmia classification
title_sort optimized convolutional neural network for arrhythmia classification
topic Q Science
url https://ir.upsi.edu.my/detailsg.php?det=9598
url-record https://ir.upsi.edu.my/detailsg.php?det=9598
Fakulti Seni, Komputeran dan Industri Kreatif
work_keys_str_mv AT shanweichen anoptimizedconvolutionalneuralnetworkforarrhythmiaclassification
AT shanweichen optimizedconvolutionalneuralnetworkforarrhythmiaclassification