Classification of lung sounds using scalogram representation of sound segments and convolutional neural network
Author:
Affiliation:
1. International School, Vietnam National University, Hanoi, Vietnam
2. School of Electronics and Telecommunications, Hanoi University of Science and Technology, Hanoi, Vietnam
Publisher
Informa UK Limited
Subject
Biomedical Engineering,General Medicine
Link
https://www.tandfonline.com/doi/pdf/10.1080/03091902.2022.2040624
Reference27 articles.
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2. Auscultation of the respiratory system
3. Mendes L, Vogiatzis IM, Perantoni E, et al. Detection of crackle events using a multi-feature approach. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2016; 2016. pp. 3679–3683.
4. Mendes L, et al. Detection of wheezes using their signature in the spectrogram space and musical features. In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) , Milan; 2015. pp. 5581–5584.
5. Lung sound classification using cepstral-based statistical features
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