Automatic Accuracy versus Complexity Characterization for Embedded Emotion-Sensing Platforms in Healthcare Applications

التفاصيل البيبلوغرافية
العنوان: Automatic Accuracy versus Complexity Characterization for Embedded Emotion-Sensing Platforms in Healthcare Applications
المؤلفون: Giovanni Mezzina, Daniela De Venuto
بيانات النشر: IEEE, 2022.
سنة النشر: 2022
مصطلحات موضوعية: Machine Learning, Emotions recognition, EEG, Machine Learning, Feature Extraction , Feature Selection, EEG, Emotions recognition, Feature Selection, Feature Extraction
اللغة: English
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c515049f36e1979561f2977aeadc20e1
http://hdl.handle.net/11589/242160
Rights: CLOSED
رقم الانضمام: edsair.doi.dedup.....c515049f36e1979561f2977aeadc20e1
قاعدة البيانات: OpenAIRE