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All Journal International Journal of Electrical and Computer Engineering
Hussein Salman, Ahmed
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Computer Science & IT Electrical & Electronics Engineering

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Employing deep learning for lung sounds classification Dhari Satea, Huda; Saleem Elameer, Amer; Hussein Salman, Ahmed; Dhari Sateaa, Shahad
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp4345-4351

Abstract

Respiratory diseases indicate severe medical problems. They cause death for more than three million people annually according to the world health organization (WHO). Recently, with corona virus disease 19 (COVID-19) spreading the situation has become extremely serious. Thus, early detection of infected people is very vital in limiting the spread of respiratory diseases and COVID-19. In this paper, we have examined two different models using convolution neural networks. Firstly, we proposed and build a convolution neural network (CNN) model from scratch for classification the lung breath sounds. Secondly, we employed transfer learning using the pre-trained network AlexNet applying on the similar dataset. Our proposed model achieved an accuracy of 0.91 whereas the transfer learning model performing much better with an accuracy of 0.94.
Co-Authors Dhari Satea, Huda Dhari Sateaa, Shahad Saleem Elameer, Amer