Beyond Grids: Scaling Up Continuous Kernels via Adaptive Point Representations for Sensor-Based Human Activity Recognition-Reference-Cited by-同舟云学术

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Beyond Grids: Scaling Up Continuous Kernels via Adaptive Point Representations for Sensor-Based Human Activity Recognition

Published:2024-08-01 Issue:15 Volume:24 Page:24211-24223
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Yao Minghui¹^ORCID,Zhang Lei¹^ORCID,Cheng Dongzhou¹^ORCID,Liu Jinsheng¹,Wang Li¹,Wu Hao²^ORCID,Song Aiguo³^ORCID

Affiliation:

1. School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, China

2. School of Information Science and Engineering, Yunnan University, Kunming, China

3. School of Instrument Science and Engineering, Southeast University, Nanjing, China

Funder

National Natural Science Foundation of China

Cultivating Plan Program for the Leader in Science and Technology of Yunnan Province, China

Ten Thousand Talent Plans for Young of Yunnan Province, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/7361/10617804/10559782.pdf?arnumber=10559782

Reference51 articles.

1. A tutorial on human activity recognition using body-worn inertial sensors

2. Sensor-based and vision-based human activity recognition: A comprehensive survey

3. Novel Human Activity Recognition and Recommendation Models for Maintaining Good Health of Mobile Users

4. Machine learning techniques for sensor-based human activity recognition with data heterogeneity—A review;Ye;arXiv:2403.15422,2024

5. Robust Human Activity Recognition via Wearable Sensors Using Dynamic Gaussian Kernel Learning

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