Name
Abstract | ||
|---|---|---|
The irregularity detection of daily behaviors has received lots of attention, especially in homecare. An IRregularity Detection (IRD) algorithm is proposed to identify the irregular behavior patterns using the unsupervised learning. The distance and similarity between daily behavior patterns are designed as important features to build up the irregularity detection model. Experiments demonstrate that the proposed algorithm exceeds the existing unsupervised machine learning algorithms in terms of the numbers of False Negative and False Positive. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICCE-Taiwan49838.2020.9258319 | 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan) |
Keywords | DocType | ISSN |
Daily behavior pattern,homecare,irregularity detection,unsupervised learning | Conference | 2575-8276 |
ISBN | Citations | PageRank |
978-1-7281-7400-6 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cuijuan Shang | 1 | 6 | 4.01 |
| chihyung chang | 2 | 25 | 10.85 |
| Bhargavi Dande | 3 | 0 | 0.68 |