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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6512052/ https://www.ncbi.nlm.nih.gov/pubmed/31183029 http://dx.doi.org/10.1155/2019/2826901 |