Research Article
ECG Classification for Detecting ECG Arrhythmia Empowered with Deep Learning Approaches
Table 2
Pseudocode of the proposed CAA-TL model.
| 1 | Start | 2 | Input ECG data from kaggle | 3 | Augmented data | 4 | ECG preprocess data | 5 | Load data & pre-trained (transfer learning) model | 6 | Trained model using transfer learning (AlexNet, SqueezeNet, and ResNet50) for ECG classification | 7 | Validation phase for ECG classification for unknown images | 8 | Compute the performance and accuracy of the proposed model | 9 | Stop |
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