Multi-HAR: Human Activity Recognition in Multi-person Scenes Based on mmWave Sensing
Author:
Affiliation:
1. School of Computer Science, Beijing University of Posts and Telecommunications,Beijing,China,100876
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10065600/10065601/10065810.pdf?arnumber=10065810
Reference18 articles.
1. Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
2. Human Activity Recognition Based on Data Fusion of FMCW Radar and Image
3. Extended kalman filter;fujii;Refernce Manual,2013
4. Activity Recognition Based on Millimeter-Wave Radar by Fusing Point Cloud and Range–Doppler Information
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1. Human Activity Recognition with Smartphones using Machine Learning Algorithm;2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS);2024-04-18
2. mFall: A Scenarios-Based Research on Human Fall Detection Leveraging Millimeter-Wave Sensing;2023 9th International Conference on Computer and Communications (ICCC);2023-12-08
3. A Hybrid Deep Neural Network with Attention Mechanism for Human Activity Recognition Based on Smartphone Sensors;2023 7th International Conference on Information Technology (InCIT);2023-11-16
4. Human-Computer Interactions Using Low-cost Millimeter Wave Radar Sensors;2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS);2023-09-25
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