Lung Sound Classification With Multi-Feature Integration Utilizing Lightweight CNN Model
Author:
Affiliation:
1. Department of Computer Science and Engineering, University of Moratuwa, Moratuwa, Sri Lanka
2. Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Valladolid, Spain
Funder
domain experts
University of Moratuwa, Sri Lanka, under the Senate Research Committee (SRC), Conference and Publishing Grant
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6287639/10380310/10419195.pdf?arnumber=10419195
Reference54 articles.
1. Prevalence and attributable health burden of chronic respiratory diseases, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017
2. Feature-Based Fusion Using CNN for Lung and Heart Sound Classification
3. A Neural Network-Based Method for Respiratory Sound Analysis and Lung Disease Detection
4. Deep Neural Network for Respiratory Sound Classification in Wearable Devices Enabled by Patient Specific Model Tuning
5. Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning
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