Active Machine Learning for Heterogeneity Activity Recognition Through Smartwatch Sensors-Reference-Cited by-同舟云学术

Active Machine Learning for Heterogeneity Activity Recognition Through Smartwatch Sensors

Published:2024 Issue: Volume:12 Page:22595-22607
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Abbas Sidra¹^ORCID,Alsubai Shtwai²^ORCID,Haque Muhammad Ibrar Ul³^ORCID,Sampedro Gabriel Avelino⁴^ORCID,Almadhor Ahmad⁵^ORCID,Hejaili Abdullah Al⁶,Ivanochko Iryna⁷^ORCID

Affiliation:

1. Department of Computer Science, COMSATS University Islamabad, Islamabad, Pakistan

2. College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia

3. Electrical Engineering Department, Sir Syed University of Engineering and Technology, Karachi, Pakistan

4. Faculty of Information and Communication Studies, University of the Philippines Open University, Los Baños, Philippines

5. Department of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia

6. Computer Science Department, Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia

7. Faculty of Management, Comenius University Bratislava, Bratislava, Slovakia

Funder

Deanship of Scientific Research at Jouf University

EU NextGenerationEU through the Recovery and Resilience Plan for Slovakia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10422809.pdf?arnumber=10422809

Reference23 articles.

1. Machine learning: a review of classification and combining techniques

2. A survey on active learning and human-in-the-loop deep learning for medical image analysis

3. Wearable sensors: A new way to track health and wellness;George;Partners Universal Int. Innov. J.,2023

4. The Future of Stress Management: Integration of Smartwatches and HRV Technology

5. Use and adoption challenges of wearable activity trackers;Shih

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