Leveraging Wearable Sensors for Human Daily Activity Recognition with Stacked Denoising Autoencoders
Activity recognition has received considerable attention in many research fields, such as industrial and healthcare fields. However, many researches about activity recognition have focused on static activities and dynamic activities in current literature, while, the transitional activities, such as...
Main Authors: | Qin Ni, Zhuo Fan, Lei Zhang, Chris D. Nugent, Ian Cleland, Yuping Zhang, Nan Zhou |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-09-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/20/18/5114 |
Similar Items
-
Radar Target Recognition Based on Stacked Denoising Sparse Autoencoder
by: Zhao Feixiang, et al.
Published: (2017-04-01) -
A Human Activity Recognition Algorithm Based on Stacking Denoising Autoencoder and LightGBM
by: Xile Gao, et al.
Published: (2019-02-01) -
Traffic Image Analysis Based on Stacked Denoising Autoencoder Neural Network
by: Daehyon Kim
Published: (2023-12-01) -
Stacked Denoising Extreme Learning Machine Autoencoder Based on Graph Embedding for Feature Representation
by: Hongwei Ge, et al.
Published: (2019-01-01) -
An Anomaly Detection Method for UAV Based on Wavelet Decomposition and Stacked Denoising Autoencoder
by: Shenghan Zhou, et al.
Published: (2024-05-01)