3 papers
cs.CV2024
Refining Remote Photoplethysmography Architectures using CKA and Empirical Methods
Nathan Vance, Patrick Flynn
Model architecture refinement is a challenging task in deep learning research fields such as remote photoplethysmography (rPPG). One architectural consideration, the depth of the m…
cs.CV2024
SiNC+: Adaptive Camera-Based Vitals with Unsupervised Learning of Periodic Signals
Jeremy Speth, Nathan Vance, Patrick Flynn +1
Subtle periodic signals, such as blood volume pulse and respiration, can be extracted from RGB video, enabling noncontact health monitoring at low cost. Advancements in remote puls…
cs.CV2024
Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity
Nathan Vance, Patrick Flynn
Domain shift differences between training data for deep learning models and the deployment context can result in severe performance issues for models which fail to generalize. We s…