Lung Sound Classification Using Co-tuning and Stochastic Normalization

Truc Nguyen; Franz Pernkopf

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arXiv · 2108.01991

Lung Sound Classification Using Co-tuning and Stochastic Normalization

Truc Nguyen·Franz Pernkopf

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Abstract

In this paper, we use pre-trained ResNet models as backbone architectures for classification of adventitious lung sounds and respiratory diseases. The knowledge of the pre-trained model is transferred by using vanilla fine-tuning, co-tuning, stochastic normalization and the combination of the co-tuning and stochastic normalization techniques. Furthermore, data augmentation in both time domain and time-frequency domain is used to account for the class imbalance of the ICBHI and our multi-channel lung sound dataset. Additionally, we apply spectrum correction to consider the variations of the recording device properties on the ICBHI dataset. Empirically, our proposed systems mostly outperform all state-of-the-art lung sound classification systems for the adventitious lung sounds and respiratory diseases of both datasets.

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BibTeX RIS

Truc Nguyen, Franz Pernkopf. 2021-08-04. Lung Sound Classification Using Co-tuning and Stochastic Normalization. https://arxiv.org/abs/2108.01991

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