VGG16-based deep learning architectures for classification of lung sounds into normal, crackles, and wheezes using Gammatonegrams
Breathing sounds are a rich source of information that can assist doctors in diagnosing pulmonary diseases in a non-invasive manner. Several algorithms can be developed based on these sounds to create an automatic classification system for lung diseases. To implement these systems, researchers...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | en |
| Published: |
2023
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| Online Access: | http://eprints.utem.edu.my/id/eprint/28048/1/VGG16-based%20deep%20learning%20architectures%20for%20classification%20of%20lung%20sounds%20into%20normal%2C%20crackles%2C%20and%20wheezes%20using%20gammatonegrams.pdf http://eprints.utem.edu.my/id/eprint/28048/ https://www.researchgate.net/publication/377242904_Advancing_Educational_Practices_Implementation_and_Impact_of_Virtual_Reality_in_Islamic_Religious_Education |
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Internet
http://eprints.utem.edu.my/id/eprint/28048/1/VGG16-based%20deep%20learning%20architectures%20for%20classification%20of%20lung%20sounds%20into%20normal%2C%20crackles%2C%20and%20wheezes%20using%20gammatonegrams.pdfhttp://eprints.utem.edu.my/id/eprint/28048/
https://www.researchgate.net/publication/377242904_Advancing_Educational_Practices_Implementation_and_Impact_of_Virtual_Reality_in_Islamic_Religious_Education