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Assessment of Electrocardiogram Rhythms by GoogLeNet Deep Neural Network Architecture
The aim of this study is to design GoogLeNet deep neural network architecture by expanding the kernel size of the inception layer and combining the convolution layers to classify the electrocardiogram (ECG) beats into a normal sinus rhythm, premature ventricular contraction, atrial premature contrac...
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| Publicado no: | J Healthc Eng |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Hindawi
2019
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6512052/ https://ncbi.nlm.nih.gov/pubmed/31183029 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2019/2826901 |
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