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Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction

IEEE Signal Processing Letters(2020)10.1109/lsp.2020.3020215Source: DataRank Database

Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction is a research paper published in IEEE Signal Processing Letters (2020). On theSindex it has a DataRank of 0. It has been cited 31 times.

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Enrichment:Funding (10 grants)OA: greenTopics (13)IDs (PubMed)

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Authors (5)

Ozan Özdenizci ORCID,Ye Wang ORCID,Toshiaki Koike–Akino ORCID,Deniz Erdoğmuş ORCID,Mo Han ORCID

Live enrichment

PubMed:33746496

National Institutes of Health

Grant: R01DC009834

U.S. Department of Health and Human Services

Grant: 90RE5017-02-01

National Science Foundation

Grant: CNS-1544895

National Science Foundation

Grant: IIS-1149570

National Science Foundation

Grant: IIS-1715858

National Science Foundation

Grant: 1544895

CPS: TTP Option: Synergy: Collaborative Research: Nested Control of Assistive Robots through Human Intent Inference

National Science Foundation

Grant: 1715858

CHS: Small: Collaborative Research: EEG-Guided Electrical Stimulation for Immersive Virtual Reality

National Institutes of Health

Grant: 3R01DC009834-10S1

Ethical Considerations for Language Modeling within Brain-Computer Interfaces

National Science Foundation

Grant: 1149570

CAREER: Signal Models, Channel Capacity, and Information Rate for Noninvasive Brain Interfaces

National Institutes of Health

Grant: 5R01DC009834-14

Optimizing BCI-FIT: Brain Computer Interface - Functional Implementation Toolkit

greenLicense: IEEE Copyright

repositoryhttps://arxiv.org/pdf/2008.11426

publisherhttps://ieeexplore.ieee.org/ielam/97/8966529/9181498-aam.pdf

publisherhttp://xplorestaging.ieee.org/ielx7/97/8966529/09181498.pdf?arnumber=9181498

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/7977990

https://doi.org/10.1109/lsp.2020.3020215

Fields of Study

0206 medical engineering0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Signal Processing (eess.SP)FOS: Computer and information sciencesComputer Science - Machine LearningStatistics - Machine LearningFOS: Electrical engineering, electronic engineering, information engineeringMachine Learning (stat.ML)Electrical Engineering and Systems Science - Signal ProcessingMachine Learning (cs.LG)adversarial deep learningstress assessment