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Detecting Respiratory Pathologies Using Convolutional Neural Networks and Variational Autoencoders for Unbalancing Data
The aim of this paper was the detection of pathologies through respiratory sounds. The ICBHI (International Conference on Biomedical and Health Informatics) Benchmark was used. This dataset is composed of 920 sounds of which 810 are of chronic diseases, 75 of non-chronic diseases and only 35 of heal...
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| Publicado no: | Sensors (Basel) |
|---|---|
| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7070339/ https://ncbi.nlm.nih.gov/pubmed/32098446 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/s20041214 |
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