VGG16-Based Deep Learning Architectures for Classification of Lung Sounds into Normal, Crackles, and Wheezes using Gammatonegrams-Reference-Cited by-同舟云学术

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VGG16-Based Deep Learning Architectures for Classification of Lung Sounds into Normal, Crackles, and Wheezes using Gammatonegrams

Published:2023-08-09 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Information Technology (ICIT)
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Author:

Zakaria Neili¹,Sundaraj Kenneth²

Affiliation:

1. University of Badji Mokhtar Annaba,Laboratoire d'Automatique et Signaux de Annaba (LASA),Electronic departement,Annaba,Algeria

2. Universiti Teknikal Malaysia Melaka,Centre for Telecommunication Research & Innovation, Fakulti Kejuruteraan Elektronik & Kejuruteraan Komputer,Durian Tunggal,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10225686/10225751/10225790.pdf?arnumber=10225790

Reference31 articles.

1. Triple-Classification of Respiratory Sounds Using Optimized S-Transform and Deep Residual Networks

2. A New Deep CNN Model for Environmental Sound Classification

3. Lung sounds classification using convolutional neural networks

4. Convolutional Neural Network for Breathing Phase Detection in Lung Sounds

5. Gammatonegram based Pulmonary Pathologies Classification using Convolutional Neural Networks

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A deep CNN-based acoustic model for the identification of lung diseases utilizing extracted MFCC features from respiratory sounds;Multimedia Tools and Applications;2024-03-12

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