Deep Wavelet Convolutional Neural Networks for Multimodal Human Activity Recognition Using Wearable Inertial Sensors

Recent advances in wearable systems have made inertial sensors, such as accelerometers and gyroscopes, compact, lightweight, multimodal, low-cost, and highly accurate. Wearable inertial sensor-based multimodal human activity recognition (HAR) methods utilize the rich sensing data from embedded multi...

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Bibliografische Detailangaben

Hauptverfasser:	Thi Hong Vuong, Tung Doan, Atsuhiro Takasu
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2023-12-01
Schriftenreihe:	Sensors
Schlagworte:	wearable inertial sensors continuous wavelet transform multimodal human activity recognition convolutional neural networks
Online-Zugang:	https://www.mdpi.com/1424-8220/23/24/9721
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