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#dcnns — Public Fediverse posts

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  1. Automatically detecting emotions from #EEGs is expected to become a major task of #BCIs. However, inaccuracies, high error rates and a lack of stability still occupy #research. A research group has now succeeded in using Deep Convolutional Neural Networks #DCNNs to classify positive, neutral and negative #emotions from EEG signals with 96% accuracy by having volunteers listen to different music.
    #Bioelectronics

    mdpi.com/2079-9292/12/10/2216

  2. Automatically detecting emotions from #EEGs is expected to become a major task of #BCIs. However, inaccuracies, high error rates and a lack of stability still occupy #research. A research group has now succeeded in using Deep Convolutional Neural Networks #DCNNs to classify positive, neutral and negative #emotions from EEG signals with 96% accuracy by having volunteers listen to different music.
    #Bioelectronics

    mdpi.com/2079-9292/12/10/2216

  3. Emotionen aus #EEGs automatisch zu erkennen, soll zu einer wesentlichen Aufgabe von #BCIs werden. Ungenauigkeiten, hohe Fehlerquoten und mangelnde Stabilität beschäftigen allerdings noch die #Forschung. Einer Arbeitsgruppe gelang es nun durch Deep Convolutional Neural Networks #DCNNs positive, neutrale und negative #Emotionen aus EEG-Signalen mit 96%iger Genauigkeit zu klassifizieren indem sie Freiwillige verschiedene Musik hören ließen.
    #Bioelektronik

    mdpi.com/2079-9292/12/10/2216