Improving Noise Robustness of Single Sensor Data in Human Activity Recognition With UMAP and Additional Data-Reference-Cited by-同舟云学术

Improving Noise Robustness of Single Sensor Data in Human Activity Recognition With UMAP and Additional Data

Published:2022-09-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 ACM International Symposium on Wearable Computers
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Author:

VU Quynh Nguyen Phuong¹^ORCID,Lago Paula²,Inoue Sozo³

Affiliation:

1. Kyushu Institute of Technology, Japan

2. Concordia University, Canada

3. Graduate School of Engineering, Kyushu Institute of Technology, Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3544794.3558465

Reference18 articles.

1. A smartphone-based fall detection system

2. Kohei Adachi , Paula Lago , Yuichi Hattori , and Sozo Inoue . 2022. Using LUPI to Improve Complex Activity Recognition . In Sensor- and Video-Based Activity and Behavior Computing, Md Atiqur Rahman Ahad, Sozo Inoue, Daniel Roggen, and Kaori Fujinami (Eds.). Springer Nature Singapore , Singapore , 39–55. Kohei Adachi, Paula Lago, Yuichi Hattori, and Sozo Inoue. 2022. Using LUPI to Improve Complex Activity Recognition. In Sensor- and Video-Based Activity and Behavior Computing, Md Atiqur Rahman Ahad, Sozo Inoue, Daniel Roggen, and Kaori Fujinami (Eds.). Springer Nature Singapore, Singapore, 39–55.

3. Improving test case selection by handling class and attribute noise

4. Critical thinking of mobile sensing for health

5. Behavior-Aware Computing: Applications and Challenges

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