most citedImproving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning-Based Audio Enhancement: Algorithm Development and Validation

22 citations · 22 across the 1 of their papers we have counts for

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eess.AS2024★ 22 cited

Improving the Robustness and Clinical Applicability of Automatic Respiratory Sound Classification Using Deep Learning-Based Audio Enhancement: Algorithm Development and Validation

Jing-Tong Tzeng, Jeng-Lin Li, Huan-Yu Chen +5

Deep learning techniques have shown promising results in the automatic classification of respiratory sounds. However, accurately distinguishing these sounds in real-world noisy con…