An Autoencoder-based Approach for Recognizing Null Class in Activities of Daily Living In-the-wild via Wearable Motion Sensors-Reference-Cited by-同舟云学术

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An Autoencoder-based Approach for Recognizing Null Class in Activities of Daily Living In-the-wild via Wearable Motion Sensors

Published:2019-05 Issue: Volume: Page:
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Container-title:ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Akbari Ali,Jafari Roozbeh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8671773/8682151/08682161.pdf?arnumber=8682161

Cited by 8 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. Statistical Database of Human Motion Recognition Using Wearable IoT—A Review;IEEE Sensors Journal;2023-07-15

2. Hierarchical Deep Learning Model with Inertial and Physiological Sensors Fusion for Wearable-Based Human Activity Recognition;ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2022-05-23

3. Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances;Sensors;2022-02-14

4. A Survey on Human Activity Recognition Using Deep Learning Techniques and Wearable Sensor Data;Communications in Computer and Information Science;2022

5. Automatic Recognition and Analysis of Balance Activity in Community-Dwelling Older Adults: Algorithm Validation;Journal of Medical Internet Research;2021-12-20

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