Context Sensitive Detection of Long-term Elderly Behavior Change
Author:
Affiliation:
1. Université Polytechnique Hauts-de-France,LAMIH UMR CNRS 8201,France
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10310305/10310314/10310468.pdf?arnumber=10310468
Reference23 articles.
1. A fusion of a deep neural network and a hidden Markov model to recognize the multiclass abnormal behavior of elderly people
2. Using Learning Techniques to Observe Elderly’s Behavior Changes over Time in Smart Home
3. Feature extraction for human activity recognition on streaming data
4. Towards online and personalized daily activity recognition, habit modeling, and anomaly detection for the solitary elderly through unobtrusive sensing
5. Unsupervised statistical concept drift detection for behaviour abnormality detection;friedrich;Appl Intell,2022
Cited by 1 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. Daily Activities Forecasting for Long-Term Elderly Behavior Change Detection;Lecture Notes in Computer Science;2024
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