3 citations · 5 across the 2 of their papers we have counts for
2 papers
eess.SP2024★ 2 cited
SPEED: Scalable Preprocessing of EEG Data for Self-Supervised Learning
Anders Gjølbye, Lina Skerath, William Lehn-Schiøler +2
Electroencephalography (EEG) research typically focuses on tasks with narrowly defined objectives, but recent studies are expanding into the use of unlabeled data within larger mod…
cs.HC2023★ 3 cited
Spectral homogeneity cross frequencies can be a quality metric for the large-scale resting EEG preprocessing
Shiang Hu, Jie Ruan, Nicolas Langer +4
The brain projects require the collection of massive electrophysiological data, aiming to the longitudinal, sectional, or populational neuroscience studies. Quality metrics automat…