GAF-GradCAM: Guided dynamic weighted fusion of temporal and frequency GAF 2D matrices for ECG-based arrhythmia detection using deep learning
This study introduces an innovative approach for arrhythmia classification that employs a Grad-CAM-guided dynamic weighted fusion of temporal and frequency features extracted from electrocardiogram (ECG) signals. By transforming ECG signals into two-dimensional Gramian Angular Field (GAF) matrices,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | Scientific African |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468227625001577 |
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