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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2019-01-01
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| Series: | Journal of Healthcare Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/2826901 |