Improving PPG Signal Classification with Machine Learning: The Power of a Second Opinion-Reference-Cited by-同舟云学术

Improving PPG Signal Classification with Machine Learning: The Power of a Second Opinion

Published:2023-06-11 Issue: Volume: Page:
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Container-title:2023 24th International Conference on Digital Signal Processing (DSP)
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Author:

Asgharnezhad Hamzeh¹,Shamsi Afshar²,Bakhshayeshi Ivan³,Alizadehsani Roohallah⁴,Chamaani Somayyeh⁵,Alinejad-Rokny Hamid⁶

Affiliation:

1. University of New South Wales,Internship in BML,Sydney,Australia

2. Concordia University,Concordia Ins. Inf. Sys. Eng,Montreal,Canada

3. University of New South Wales,BioMedical Machine Learning Lab,Sydney,Australia

4. Deakin University,Int. Sys. Research and Innovation (IISRI),Geelong,Australia

5. K.N. Toosi University of Technology,Faculty of Electrical Engineering,Tehran,Iran

6. University of New South Wales,BioMedical Machine Learning Lab (BML),Sydney,Australia

Publisher

IEEE

Link

Reference17 articles.

3. Dropout as a bayesian approximation: Representing model uncertainty in deep learning;gal;International Conference on Machine Learning,2016

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