Asymmetric Residual Neural Network for Accurate Human Activity Recognition

Asymmetric Residual Neural Network for Accurate Human Activity Recognition

Human activity recognition (HAR) using deep neural networks has become a hot topic in human−computer interaction. Machines can effectively identify human naturalistic activities by learning from a large collection of sensor data. Activity recognition is not only an interesting research pro...

Full description

Bibliographic Details
Main Authors: Jun Long, Wuqing Sun, Zhan Yang, Osolo Ian Raymond
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Information
Subjects:
human activity recognition
deep neural network
residual networks
spatial features
temporal features
Online Access:https://www.mdpi.com/2078-2489/10/6/203

Internet

https://www.mdpi.com/2078-2489/10/6/203

Similar Items