A robust convolutional neural network for online smartphone-based human activity recognition-Reference-Cited by-同舟云学术

A robust convolutional neural network for online smartphone-based human activity recognition

Published:2018-08-26 Issue:2 Volume:35 Page:1609-1620
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Almaslukh Bandar¹,Al Muhtadi Jalal¹,Artoli Abdel Monim¹

Affiliation:

1. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference28 articles.

1. A survey on human activity recognition using wearable sensors;Lara;IEEE Communications Surveys and Tutorials,2013

2. Online human activity recognition on smart phones;Kose;Workshop From Smartphones and Wearables to Big Data on Mobile Sensing,2012

3. Das S. , Green L. , Perez B. , Murphy M. and Perring A. , Detecting user activities using the accelerometer on android smartphones, TRUST REU The Team for Research in Ubiquitous Secure Technology 29.

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