Data augmentation using variational autoencoders for improvement of respiratory disease classification

HIGHLIGHTS

  • who: Jane Saldanha and collaborators from the International (Deemed University), Pune, Maharashtra, India, Deptof Computer Science, Symbiosis have published the Article: Data augmentation using Variational Autoencoders for improvement of respiratory disease classification, in the Journal: PLOS ONE of 21/08/2021
  • what: The work shows that deep learningbased lung sound classification models are not only promising solution over traditional methods but can also achieve significant performance boost upon augmenting an imbalanced training set. The first reason for creating synthetic samples is to avoid the usage of original samples for privacy reasons. This work has explored . . .

     

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