| COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings M Pahar, M Klopper, R Warren, T Niesler Computers in Biology and Medicine 135, 104572, 2021 | 297 | 2021 |
| COVID-19 detection in cough, breath and speech using deep transfer learning and bottleneck features M Pahar, M Klopper, R Warren, T Niesler Computers in Biology and Medicine 141, 105153, 2022 | 89 | 2022 |
| Automatic cough classification for tuberculosis screening in a real-world environment M Pahar, M Klopper, B Reeve, G Theron, R Warren, T Niesler Physiological Measurement 42 (10), 2021 | 70 | 2021 |
| Reduced firing rates of high threshold motor units in response to eccentric overload TG Balshaw, M Pahar, R Chesham, LJ Macgregor, AM Hunter Physiological reports 5 (2), e13111, 2017 | 25 | 2017 |
| Deep Neural Network based Cough Detection using Bed-mounted Accelerometer Measurements M Pahar, I Miranda, A Diacon, T Niesler ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 24 | 2021 |
| Automatic Tuberculosis and COVID-19 cough classification using deep learning M Pahar, M Klopper, B Reeve, R Warren, G Theron, A Diacon, T Niesler 2022 International Conference on Electrical, Computer and Energy …, 2022 | 18 | 2022 |
| Automatic non-invasive Cough Detection based on Accelerometer and Audio Signals M Pahar, I Miranda, A Diacon, T Niesler Journal of Signal Processing Systems, 1-15, 2022 | 18 | 2022 |
| Machine learning based COVID-19 detection from smartphone recordings: cough, breath and speech M Pahar, T Niesler arXiv e-prints, arXiv: 2104.02477, 2021 | 16 | 2021 |
| Coding and Decoding Speech using a Biologically Inspired Coding System M Pahar, LS Smith 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 3025-3032, 2020 | 14 | 2020 |
| Accelerometer-based bed occupancy detection for automatic, non-invasive long-term cough monitoring M Pahar, I Miranda, A Diacon, T Niesler IEEE Access 11, 30739-30752, 2023 | 13 | 2023 |
| Machine Learning Prediction of Hospitalization due to COVID-19 based on Self-Reported Symptoms: A Study for Brazil I Miranda, G Cardoso, M Pahar, G Oliveira, T Niesler 2021 IEEE EMBS International Conference on Biomedical and Health Informatics …, 2021 | 6 | 2021 |
| Automatic Tuberculosis detection in cough patterns using NLP-style cough embeddings M Pahar, G Theron, T Niesler 2022 International Conference on Engineering and Emerging Technologies …, 2022 | 4 | 2022 |
| Wake-Cough: cough spotting and cougher identification for personalised long-term cough monitoring M Pahar, M Klopper, B Reeve, R Warren, G Theron, A Diacon, T Niesler 2022 30th European Signal Processing Conference (EUSIPCO), 185-189, 2022 | 4 | 2022 |
| ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing M Pahar, I Miranda, A Diacon, T Niesler ICASSP, 2021 | 4 | 2021 |
| COVID-19 Detection in Cough M Pahar, M Klopper, R Warren, T Niesler Breath and Speech using Deep Transfer Learning and Bottleneck Features, 2021 | 3 | 2021 |
| A novel sound reconstruction technique based on a spike code (event) representation M Pahar University of Stirling, 2016 | 3 | 2016 |
| Cough as Noninvasive Biomarker for Monitoring Tuberculosis Treatment: A Proof-of-Concept Study S Janssen, CM Upton, VR De Jager, A Faraj, M Pahar, IDS Miranda, ... Annals of the American Thoracic Society 20 (12), 1822-1825, 2023 | 1 | 2023 |
| Deep Transfer Learning based COVID-19 Detection in Cough, Breath and Speech using Bottleneck Features M Pahar, T Niesler | 1 | 2021 |
| Reconstructing sound from its coded state in a Spike Based System M Pahar | 1 | 2012 |
| RECREATING SOUNDS & DELAY SENSITIVITY IN RECONSTRUCTION OF A MULTI-BAND SPIKE BASED CODING OF AN AUDIO SIGNAL M Pahar | 1 | 2011 |
Thomas NieslerDepartment of Electrical and Electronic Engineering, University of Stellenbosch, South Africa在 sun.ac.za 的电子邮件经过验证
