Development of an Integrated Approach and Automated Tools for Determining the Emotional State of a Human, Using Various Types of Digital Context

Author:

Zubkov A. V.,Rozaliev V. L.,Orlova Yu. A.

Publisher

Springer International Publishing

Reference17 articles.

1. Chew, Y.H., Wong, L.K., See, J., et al.: LiteEmo: lightweight deep neural networks for image emotion recognition (2019). https://doi.org/10.1109/mmsp.2019.8901699

2. .NET language binding special information (2019). http://developer.tobiipro.com/dotnet.html. Accessed 08 Mar 2019

3. Github (2018). https://github.com/Emotiv/community-sdk. Accessed 07 Dec 2019

4. Kozarenko, V.A.: The Giordano memorization system. Mnemocon, Moscow (2007)

5. Zubkov, A.V., Kamennov, Ya.E., Orlova, Yu.A., et al.: Study of models of brain activity using a neurointerface. In: Innovative, Information and Communication Technologies: Collection of Articles, Sochi, 1–10 October 2019, pp. 187–191 (2019)

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