Transfer Learning Approaches for the Identification of Lung Respiratory Sounds

Registration ID: IJNRD_215638

Published ID: IJNRD2403511

DOI: Click Here to Get

Dhir Shah , Simran Deshmukh , Dhrumil Jaiswal

: The sounds produced by the lungs when breathing might provide important information to physicians. Based on our findings, we recommend a deep learning-based approach to the prediction of breathing-related lung sounds. The Proposed model was trained in lung sounds collected from people suffering from a broad variety of respiratory conditions. The research improves classifying lung sounds, by audio to image spectrogram features is taken and used to train a deep convolutional neural network.

Published Paper   E-Certificate

Dhir Shah, Simran Deshmukh, & Dhrumil Jaiswal (March-2024). Transfer Learning Approaches for the Identification of Lung Respiratory Sounds. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), f86-f91. https://ijnrd.org/papers/IJNRD2403511.pdf

Volume 9 Issue 3, March-2024

Pages : f86-f91

Paper Reg. ID: IJNRD_215638

Published Paper Id: IJNRD2403511

Downloads: 000121983

Research Area: Computer Science & Technology 

Country: Vadodara, Gujarat, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2403511.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403511

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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