This project is about classifying respiratory sounds using Attention and Vision Transformer on ICBHI dataset..

RDLINet: A Novel Lightweight Inception Network for Respiratory Disease Classification Using Lung Sounds (IEEE TIM-2024)

AsTFSONN: A Unified Framework Based on Time-Frequency Domain Self-Operational Neural Network for Asthmatic Lung Sound Classification (IEEE MeMeA-2024)

Official Implementation of Non-Contrastive Self-Supervised Learning with UNO Process for Respiratory Sound Analysis

Code accompanying ESANN 2025 submission "Real-Time Adventitious Lung Sound Event Detection: Assessing the Need for Breathing Cycle Segmentation". Dataset used was ICBHI 2017.

A Novel Multi-Head Self-Organized Operational Neural Network Architecture for Chronic Obstructive Pulmonary Disease Detection Using Lung Sounds (IEEE TASLP-2024)

Pulmo-TS2ONN: A Novel Triple Scale Self Operational Neural Network for Pulmonary Disorder Detection Using Respiratory Sounds (IEEE TIM-2024)