Feature Selection for Activity Recognition from Smartphone Accelerometer Data-Reference-Cited by-同舟云学术

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Feature Selection for Activity Recognition from Smartphone Accelerometer Data

Published:2017-07-18 Issue: Volume: Page:1-9
ISSN:1079-8587
Container-title:Intelligent Automation & Soft Computing
language:en
Short-container-title:Intelligent Automation & Soft Computing

Author:

Quiroz Juan C.¹,Banerjee Amit²,Dascalu Sergiu M.³,Lau Sian Lun¹

Affiliation:

1. Department of Computing and Information Systems, Sunway University, Bandar Sunway, Malaysia

2. School of Science, Engineering and Technology, Penn State Harrisburg, Middletown, USA

3. Department of Computer Science and Engineering, University of Nevada, Reno, USA

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Software

Reference17 articles.

1. Ambient Assisted Living and Home Care

2. Activity Recognition from User-Annotated Acceleration Data

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1. Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson’s Disease;Sensors;2024-08-01

2. Human activity recognition: A comprehensive review;Expert Systems;2024-07-27

3. Permutation importance based modified guided regularized random forest in human activity recognition with smartphone;Engineering Applications of Artificial Intelligence;2024-03

4. Time-Series Data to Refined Insights: A Feature Engineering-Driven Approach to Gym Exercise Recognition;IEEE Access;2024

5. Activity recognition for elderly care using genetic search;Computer Science and Information Systems;2024

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