Patch-Mix Contrastive Learning with Audio Spectrogram Transformer on Respiratory Sound Classification (INTERSPEECH 2023)

Implementation of IEEE Access paper - Lung Sound Recognition Algorithm Based on VGGish-BiGRU

RespireNet is an innovative web-based application that harnesses the capabilities of deep learning and Mel-frequency cepstral coefficients (MFCC) as a feature extraction technique for accurate respiratory disease prediction. The primary objective of this user-friendly web application is to facilitate early detection.

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

VGAResNet: A Unified Visibility Graph Adjacency Matrix-Based Residual Network for Chronic Obstructive Pulmonary Disease Detection Using Lung Sounds

[ICASSP 2024] Multi-View Spectrogram Transformer for Respiratory Sound Classification

AsthmaSCELNet: A Lightweight Supervised Contrastive Embedding Learning Framework For Asthma Classification Using Lung Sounds (INTERSPEECH 2024)

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

COPD severity grading using lung sounds and machine learning

Signal processing project repo

Respiratory Sound Dataset is a refined collection of respiratory sound recordings sourced from Kaggle, designed for machine learning applications focused on detecting lung conditions such as wheezes and crackles. The dataset includes high-quality audio files, annotations, and metadata, making it suitable for research in respiratory health.

ILDNet: A Novel Deep Learning Framework for Interstitial Lung Disease Identification Using Respiratory Sounds (IEEE SPCOM-2024)

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)