A Study of Machine Learning Techniques based on Human Daily Living Activities via Inertial Sensors-Reference-Cited by-同舟云学术

A Study of Machine Learning Techniques based on Human Daily Living Activities via Inertial Sensors

Published:2023-03-08 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD)
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Author:

Mustafa Zaid¹

Affiliation:

1. Al-Balqa Applied University,Faculty of Information and Communication Technology,Department of Computer Information Systems Prince Abdullah Bin Ghazi,Al-Salt,Jordan,19117

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099474/10099500/10099820.pdf?arnumber=10099820

Reference48 articles.

1. Recognition of daily routines and accidental event with multipoint wearable inertial sensing for seniors home care

2. A Comparative Analysis of Hybrid Deep Learning Models for Human Activity Recognition

3. Performance Analysis of Smartphone-Sensor Behavior for Human Activity Recognition

4. Sensor Based Human Activity Recognition Using Adaboost Ensemble Classifier

5. On the use of ensemble of classifiers for accelerometer-based activity recognition

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1. Recognition of Daily Activities in Adults With Wearable Inertial Sensors: Deep Learning Methods Study;JMIR Medical Informatics;2024-08-09

2. Recognition of Daily Activities in Adults With Wearable Inertial Sensors: Deep Learning Methods Study (Preprint);2024-02-05

3. Wearable Sensors-Based Human Activity Recognition with Deep Convolutional Neural Network and Fuzzy Classification;Wireless Personal Communications;2023-11