MFCC matrices with 13 coefficients and adaptive windowing plus direct concatenation outperform log-mel spectrograms and VAR models for asthma-COPD classification, reaching F1 scores of 0.877 (cycle) and 0.855 (subject).
Measuring overfitting in convolutional neural networks using adversarial perturbations and label noise.arXiv preprint arXiv:2209.13382, 2022
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Optimizing 2D Input Representations and Sub-phase Fusion Strategies for Differential Diagnosis of Asthma and COPD Using CNN- and GRU-Based Networks
MFCC matrices with 13 coefficients and adaptive windowing plus direct concatenation outperform log-mel spectrograms and VAR models for asthma-COPD classification, reaching F1 scores of 0.877 (cycle) and 0.855 (subject).