ALAE-TAE-CutMix+: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors-Reference-Cited by-同舟云学术

ALAE-TAE-CutMix+: Beyond the State-of-the-Art for Human Activity Recognition Using Wearable Sensors

Published:2023-03-13 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Pervasive Computing and Communications (PerCom)
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Author:

Ahmad Nafees¹,Leung Ho-fung¹

Affiliation:

1. The Chinese University of Hong Kong,Department of Computer Science and Engineering,Hong Kong SAR,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10099036/10099057/10099138.pdf?arnumber=10099138

Reference29 articles.

1. Squeeze-and-Excitation Networks

2. Pd disease state assessment in naturalistic environments using deep learning;yannick hammerla;Twenty-Ninth AAAI Conference on Artificial Intelligence,0

3. Convolutional neural networks for human activity recognition using body-worn sensors;moya rueda;Informatics,2018

4. A Survey on Human Activity Recognition using Wearable Sensors

5. Deep, con-volutional, and recurrent models for human activity recognition using wearables;hammerla;Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence IJCAI'16,0

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