HARNAS: Human Activity Recognition Based on Automatic Neural Architecture Search Using Evolutionary Algorithms

Human activity recognition (HAR) based on wearable sensors is a promising research direction. The resources of handheld terminals and wearable devices limit the performance of recognition and require lightweight architectures. With the development of deep learning, the neural architecture search (NA...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 21; H. 20; S. 6927
Hauptverfasser:	Wang, Xiaojuan, Wang, Xinlei, Lv, Tianqi, Jin, Lei, He, Mingshu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 19.10.2021 MDPI
Schlagworte:	Accuracy Automation Back propagation Classification Datasets Deep learning Discriminant analysis Genetic algorithms human activity recognition Machine learning multi-objective optimization multimodal sensor data neural architecture search Neural networks Optimization Sensors Wearable computers
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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