S
Seul-Ki Yeom
Researcher at Korea University
Publications - 16
Citations - 550
Seul-Ki Yeom is an academic researcher from Korea University. The author has contributed to research in topics: Unconsciousness & Electroencephalography. The author has an hindex of 8, co-authored 16 publications receiving 385 citations. Previous affiliations of Seul-Ki Yeom include Technical University of Berlin.
Papers
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Journal ArticleDOI
Network Properties in Transitions of Consciousness during Propofol-induced Sedation.
Minji Lee,Robert D. Sanders,Seul-Ki Yeom,Dong-Ok Won,Kwang-Suk Seo,Hyun Jeong Kim,Giulio Tononi,Seong-Whan Lee +7 more
TL;DR: Network changes using graph theoretical analysis of high-density EEG during patient-titrated propofol-induced sedation provide novel insights into the neural correlates of these behavioural transitions and EEG signatures for monitoring the levels of consciousness under sedation.
Journal ArticleDOI
Pruning by explaining: A novel criterion for deep neural network pruning
Seul-Ki Yeom,Philipp Seegerer,Sebastian Lapuschkin,Alexander Binder,Alexander Binder,Simon Wiedemann,Klaus-Robert Müller,Wojciech Samek +7 more
TL;DR: This paper proposes a novel criterion for CNN pruning inspired by neural network interpretability: the most relevant elements, i.e. weights or filters, are automatically found using their relevance scores obtained from concepts of explainable AI (XAI).
Journal ArticleDOI
Person authentication from neural activity of face-specific visual self-representation
TL;DR: A novel stimulus presentation paradigm, using self-face and non-self-face images as stimuli for a person authentication system that can validate a person's identity by comparing the observed trait with those stored in the database (one-to-one matching).
Journal ArticleDOI
An efficient ERP-based brain-computer interface using random set presentation and face familiarity.
TL;DR: Stronger deflections of the ERPs in response to face stimuli are indicated, which are further enhanced when using the self-face images, and thereby improving P300-based spelling performance and leading to a significant reduction of stimulus sequences required for correct character classification.
Journal ArticleDOI
Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol
Seul-Ki Yeom,Dong-Ok Won,Seong In Chi,Kwang-Suk Seo,Hyun Jeong Kim,Klaus Robert Müller,Seong-Whan Lee +6 more
TL;DR: Compared with general anesthesia, the results provide insights into critical hallmarks of sedative-induced (un)consciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and the sedative used.