Robust Human Activity Recognition via Wearable Sensors Using Dynamic Gaussian Kernel Learning-Reference-Cited by-同舟云学术

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

Published:2024-03-15 Issue:6 Volume:24 Page:8265-8280
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Wang Shuaishuai¹^ORCID,Sun Yixiang²^ORCID,Sha Yetong¹,Yang Guangyu¹^ORCID,Cheng Dongzhou¹^ORCID,Zhang Lei¹^ORCID,Wu Hao³^ORCID,Song Aiguo⁴^ORCID

Affiliation:

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

2. Department of Computer Science, Brown University, Providence, RI, USA

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

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

Funder

National Nature Science Foundation of China

Industry-Academia Cooperation Innovation Fund Projection of Jiangsu Province

Yunnan Provincial Foundation for Leaders of Disciplines in Science and Technology

Yunnan High-Level Talent Training Support Plan: Young Top Talent Special Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/7361/10472410/10413952.pdf?arnumber=10413952

Reference55 articles.

1. A multibranch CNN-BiLSTM model for human activity recognition using wearable sensor data

2. Pattern identification of different human joints for different human walking styles using inertial measurement unit (IMU) sensor

3. Continuous Hidden Markov Model for Pedestrian Activity Classification and Gait Analysis

4. Learning Disentangled Representation for Mixed- Reality Human Activity Recognition With a Single IMU Sensor

5. Smartphone Sensor-Based Human Activity Recognition Using Feature Fusion and Maximum Full a Posteriori

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Beyond Grids: Scaling Up Continuous Kernels via Adaptive Point Representations for Sensor-Based Human Activity Recognition;IEEE Sensors Journal;2024-08-01

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