检索结果 - Klaus‐Robert Müller

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  1. 1
    Transferring Subspaces Between Subjects in Brain--Computer Interfacing

    Transferring Subspaces Between Subjects in Brain--Computer Interfacing 由 Wojciech Samek, Frank C. Meinecke, Klaus‐Robert Müller

    出版 2013
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  2. 2
    A convolutional neural network for steady state visual evoked potential classification under ambulatory environment

    A convolutional neural network for steady state visual evoked potential classification under ambulatory environment 由 No-Sang Kwak, Klaus‐Robert Müller, Seong‐Whan Lee

    出版 2017
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  3. 3
    Ensembles of adaptive spatial filters increase BCI performance: an online evaluation

    Ensembles of adaptive spatial filters increase BCI performance: an online evaluation 由 Claudia Sannelli, Carmen Vidaurre, Klaus‐Robert Müller, Benjamin Blankertz

    出版 2016
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  4. 4
    A large scale screening study with a SMR-based BCI: Categorization of BCI users and differences in their SMR activity

    A large scale screening study with a SMR-based BCI: Categorization of BCI users and differences in their SMR activity 由 Claudia Sannelli, Carmen Vidaurre, Klaus‐Robert Müller, Benjamin Blankertz

    出版 2019
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  5. 5
    Interpretable deep neural networks for single-trial EEG classification

    Interpretable deep neural networks for single-trial EEG classification 由 Irene Sturm, Sebastian Lapuschkin, Wojciech Samek, Klaus‐Robert Müller

    出版 2016
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  6. 6
    Brain-Switches for Asynchronous Brain–Computer Interfaces: A Systematic Review

    Brain-Switches for Asynchronous Brain–Computer Interfaces: A Systematic Review 由 Chang Hee Han, Klaus‐Robert Müller, Han-Jeong Hwang

    出版 2020
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  7. 7
    Predicting BCI performance to study BCI illiteracy

    Predicting BCI performance to study BCI illiteracy 由 Thorsten Dickhaus, Claudia Sannelli, Klaus‐Robert Müller, Gabriel Curio, Benjamin Blankertz

    出版 2009
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  8. 8
    An Efficient ERP-Based Brain-Computer Interface Using Random Set Presentation and Face Familiarity

    An Efficient ERP-Based Brain-Computer Interface Using Random Set Presentation and Face Familiarity 由 Seul-Ki Yeom, Siamac Fazli, Klaus‐Robert Müller, Seong‐Whan Lee

    出版 2014
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  9. 9
    Modeling Sparse Connectivity Between Underlying Brain Sources for EEG/MEG

    Modeling Sparse Connectivity Between Underlying Brain Sources for EEG/MEG 由 Stefan Haufe, Ryota Tomioka, Guido Nolte, Klaus‐Robert Müller, Motoaki Kawanabe

    出版 2010
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  10. 10
    Analyzing Neuroimaging Data Through Recurrent Deep Learning Models

    Analyzing Neuroimaging Data Through Recurrent Deep Learning Models 由 Armin W. Thomas, Hauke R. Heekeren, Klaus‐Robert Müller, Wojciech Samek

    出版 2019
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  11. 11
    True Zero-Training Brain-Computer Interfacing – An Online Study

    True Zero-Training Brain-Computer Interfacing – An Online Study 由 Pieter-Jan Kindermans, Martijn Schreuder, Benjamin Schrauwen, Klaus‐Robert Müller, Michael Tangermann

    出版 2014
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  12. 12
    Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters

    Predicting BCI Subject Performance Using Probabilistic Spatio-Temporal Filters 由 Heung‐Il Suk, Siamac Fazli, Jan Mehnert, Klaus‐Robert Müller, Seong‐Whan Lee

    出版 2014
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  13. 13
    A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface

    A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface 由 Benjamin Blankertz, Matthias Krauledat, Guido Dornhege, John Williamson, Roderick Murray‐Smith, Klaus‐Robert Müller

    出版 2007
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  14. 14
    Stereoscopic depth increases intersubject correlations of brain networks

    Stereoscopic depth increases intersubject correlations of brain networks 由 Michael Gaebler, Felix Bießmann, Jan-Peter Lamke, Klaus‐Robert Müller, Henrik Walter, Stefan Hetzer

    出版 2014
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  15. 15
    Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis

    Improved physiological noise regression in fNIRS: A multimodal extension of the General Linear Model using temporally embedded Canonical Correlation Analysis 由 Alexander von Lühmann, Xinge Li, Klaus‐Robert Müller, David A. Boas, Meryem A. Yücel

    出版 2019
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  16. 16
    DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies

    DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies 由 Bettina Mieth, Alexandre Rozier, Juan Antonio Rodríguez, Marina Höhne, Nico Görnitz, Klaus‐Robert Müller

    出版 2021
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  17. 17
    Enhanced performance by a hybrid NIRS–EEG brain computer interface

    Enhanced performance by a hybrid NIRS–EEG brain computer interface 由 Siamac Fazli, Jan Mehnert, Jens Steinbrink, Gabriel Curio, Arno Villringer, Klaus‐Robert Müller, Benjamin Blankertz

    出版 2011
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  18. 18
    Motor Imagery for Severely Motor-Impaired Patients: Evidence for Brain-Computer Interfacing as Superior Control Solution

    Motor Imagery for Severely Motor-Impaired Patients: Evidence for Brain-Computer Interfacing as Superior Control Solution 由 Johannes Höhne, Elisa Mira Holz, Pit Staiger-Sälzer, Klaus‐Robert Müller, Andrea Kübler, Michael Tangermann

    出版 2014
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  19. 19
    Patient-level proteomic network prediction by explainable artificial intelligence

    Patient-level proteomic network prediction by explainable artificial intelligence 由 Philipp Keyl, Michael Bockmayr, Daniel Heim, Gabriel Dernbach, Grégoire Montavon, Klaus‐Robert Müller, Frederick Klauschen

    出版 2022
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  20. 20
    EEG-based classification of video quality perception using steady state visual evoked potentials (SSVEPs)

    EEG-based classification of video quality perception using steady state visual evoked potentials (SSVEPs) 由 Laura Acqualagna, Sebastian Bosse, Anne K. Porbadnigk, Gabriel Curio, Klaus‐Robert Müller, Thomas Wiegand, Benjamin Blankertz

    出版 2015
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