MFE-HAR
Author:
Affiliation:
1. Macquarie University, Sydney, NSW, Australia
2. Zhejiang University of Technology, Hangzhou, China
3. University of Technology Sydney, Sydney, NSW, Australia
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3360774.3360787
Reference26 articles.
1. Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison with State-of-the-Art Algorithms Using a Benchmark Dataset
Cited by 7 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. SensorNet: An Adaptive Attention Convolutional Neural Network for Sensor Feature Learning;Sensors;2024-05-21
2. A Hierarchical Multitask Learning Approach for the Recognition of Activities of Daily Living Using Data from Wearable Sensors;Sensors;2023-10-03
3. Research on Feature Selection of Human Physical Activity Recognition for IOT Wearable Devices;2021 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD);2021-10-21
4. Do You Brush Your Teeth Properly? An Off-body Sensor-based Approach for Toothbrushing Monitoring;2021 IEEE International Conference on Digital Health (ICDH);2021-09
5. Dataset for toothbrushing activity using brush-attached and wearable sensors;Data in Brief;2021-08
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