A Novel Exploitative and Explorative GWO-SVM Algorithm for Smart Emotion Recognition

Emotion recognition or detection is broadly utilized in patient-doctor interactions for diseases, such as schizophrenia and autism and the most typical techniques are speech detection and facial recognition. However, features extracted from these behavior-based emotion recognitions are not reliable...

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Veröffentlicht in:	IEEE internet of things journal Jg. 10; H. 11; S. 9999 - 10011
Hauptverfasser:	Yan, Xucun, Lin, Zihuai, Lin, Zhiyun, Vucetic, Branka
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.06.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms Artificial neural networks Autism Biomedical monitoring Datasets Electrocardiogram (ECG) signals Electrocardiography Embedded systems Emotion recognition Emotions Face recognition Feature extraction Feature recognition gray wolf optimizer (GWO) Internet of Things Internet of Things (IoT) Lightweight Machine learning Schizophrenia smart health Supervised learning support vector machine (SVM) Support vector machines
ISSN:	2327-4662, 2327-4662
Online-Zugang:	Volltext
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