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Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches

Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches

Mohammad Moulaeifard
Loic Coquelin
Mantas Rinkevičius
Andrius Sološenko
Oskar Pfeffer
Ciaran Bench
Nando Hegemann
Sara Vardanega
Manasi Nandi
Jordi Alastruey
Christian Heiss
Vaidotas Marozas
Andrew Thompson
Philip Aston
Peter H. Charlton
Nils Strodthoff
    OOD
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Papers citing "Machine-learning for photoplethysmography analysis: Benchmarking feature, image, and signal-based approaches"

2 / 2 papers shown
Title
Generalizable deep learning for photoplethysmography-based blood pressure estimation -- A Benchmarking Study
Generalizable deep learning for photoplethysmography-based blood pressure estimation -- A Benchmarking Study
Mohammad Moulaeifard
Peter H. Charlton
Nils Strodthoff
OOD
91
1
0
26 Feb 2025
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
277
43,511
0
17 Sep 2014

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