A Semi-Supervised Algorithm for Improving the Consistency of Crowdsourced Datasets: The COVID-19 Case Study on Respiratory Disorder Classification

9 September 2022

Papers citing "A Semi-Supervised Algorithm for Improving the Consistency of Crowdsourced Datasets: The COVID-19 Case Study on Respiratory Disorder Classification"

4 / 4 papers shown

Title
Robust COVID-19 Detection from Cough Sounds using Deep Neural Decision Tree and Forest: A Comprehensive Cross-Datasets Evaluation Rofiqul Islam N. K. Chowdhury Muhammad Ashad Kabir 30 0 0 03 Jan 2025
How to Count Coughs: An Event-Based Framework for Evaluating Automatic Cough Detection Algorithm Performance Lara Orlandic Jonathan Dan Jérôme Thevenot T. Teijeiro Alain Sauty David Atienza 34 2 0 03 Jun 2024
Detecting COVID-19 from Breathing and Coughing Sounds using Deep Neural Networks Björn W. Schuller H. Coppock Alexander Gaskell 35 63 0 29 Dec 2020
SMOTE: Synthetic Minority Over-sampling Technique Nitesh V. Chawla Kevin W. Bowyer Lawrence Hall W. Kegelmeyer AI4TS 160 25,214 0 09 Jun 2011