Post-hoc Labeling of Arbitrary M/EEG Recordings for Data-Efficient Evaluation of Neural Decoding Methods

Overview of attention for article published in Frontiers in Neuroinformatics, August 2019

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Since the rise of #BCI systems, effort has been put into developing novel techniques for decoding neural sources from noisy M/#EEG recordings using linear and nonlinear methods. This paper proposes an alternative for data-efficient evaluation. @bciplus htt

17 Oct 2019

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RT @FrontNeurosci: New Research: New Research: Post-hoc Labeling of Arbitrary M/EEG Recordings for Data-Efficient Evaluation of Neural Deco…

04 Aug 2019

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RT @FrontNeurosci: New Research: New Research: Post-hoc Labeling of Arbitrary M/EEG Recordings for Data-Efficient Evaluation of Neural Deco…

04 Aug 2019

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RT @FrontNeurosci: New Research: New Research: Post-hoc Labeling of Arbitrary M/EEG Recordings for Data-Efficient Evaluation of Neural Deco…

04 Aug 2019

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