A study on IMU-Based Human Activity Recognition Using Deep Learning and Traditional Machine Learning-Reference-Cited by-同舟云学术

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A study on IMU-Based Human Activity Recognition Using Deep Learning and Traditional Machine Learning

Published:2020-05 Issue: Volume: Page:
ISSN:
Container-title:2020 5th International Conference on Computer and Communication Systems (ICCCS)
language:
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Author:

Hou Chengli

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9114888/9118408/09118506.pdf?arnumber=9118506

Cited by 26 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. Vector-based Inertial Poser: Human pose estimation with high gain observer and deep learning using sparse IMU sensors;Biomedical Signal Processing and Control;2024-09

2. Privacy preservation in sensor-based Human Activity Recognition through autoencoders for low-power IoT devices;Internet of Things;2024-07

3. Beyond Thresholds: A General Approach to Sensor Selection for Practical Deep Learning-based HAR;2024 IEEE/ACM Ninth International Conference on Internet-of-Things Design and Implementation (IoTDI);2024-05-13

4. A Bilateral Assessment of Human Activities Using PSO-Based Feature Optimization and Non-linear Multi-task Least Squares Twin Support Vector Machine;SN Computer Science;2024-03-13

5. Complexity-aware Features Selection for Wrist-worn Human Activity Recognition;2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops);2024-03-11

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