Denoising UWB Radar Data for Human Activity Recognition Using Convolutional Autoencoders

Human Activity Recognition (HAR) is one of the most popular research topics thanks to its usefulness in providing targeted, meaningful assistance to older adults. Because of the aging of the population in first-world countries, it becomes increasingly important to find innovative solutions that redu...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access Jg. 11; S. 1
Hauptverfasser:	Lafontaine, Virgile, Bouchard, Kevin, Maitre, Julien, Gaboury, Sebastien
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Activity of daily living Ambient intelligence Artificial neural networks Background noise Convolutional neural networks data filtering data processing Datasets deep learning Feature extraction Filtration Human activity recognition Monitoring Noise reduction Radar data Sensors Smart buildings Ultra wideband radar Ultrawideband radar unsupervised learning UWB radars
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!