Ph.D. Research Work Description

Basic research objectives:

Below the graphical abstract provides a basic overview of the research problem

Pulmonary disorder detection using respiratory sounds

A. Roy and U. Satija, "RDLINet: A Novel Lightweight Inception Network for Respiratory Disease Classification Using Lung Sounds," in IEEE Transactions on Instrumentation and Measurement (Impact factor: 5.6, Q1, h5 index: 83), vol. 72, pp. 1-13, 2023, Art no. 4008813, DOI: 10.1109/TIM.2023.3292953.

COPD severity classification using respiratory sounds

A. Roy and U. Satija, "A Novel Melspectrogram Snippet Representation Learning Framework For Severity Detection of Chronic Obstructive Pulmonary Diseases," in IEEE Transactions on Instrumentation and Measurement (Impact factor: 5.6, Q1, h5 index: 83), vol. 72, pp. 1-11, 2023, Art no. 4003311, DOI: 10.1109/TIM.2023.3256468

GitHub Repository QR

Asthma identification using respiratory sounds using contrastive supervised embedding learning framework: AsthmaSCELNet

A. Roy, U. Satija, "AsthmaSCELNet: A Lightweight Supervised Contrastive Embedding Learning Framework For Asthma Classification Using Lung Sounds", Proc. INTERSPEECH (Core-A*, h5 index: 107), Dublin, Ireland, 2023, 5431-5435, doi: 10.21437/Interspeech.2023-428.

Asthma identification using respiratory sounds using time-frequency self-operational neural network: AsTFSONN: