Name
Title | ||
|---|---|---|
A Dense Margin Network for Human Activity Recognition Based on Augmented Channel State Information |
Abstract | ||
|---|---|---|
Human activity recognition based on channel state information (CSI) has received widespread attention in recent years due to its low cost and privacy protection. However, its accuracy can be significantly reduced when most of the current recognition approaches are applied to new users who have not participated in model training. To address this issue, a new passive human activity recognition metho... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/SWC50871.2021.00019 | 2021 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/IOP/SCI) |
Keywords | DocType | ISBN |
WiFi,Channel State Information,Human activity recognition,CycleGAN,CosFace | Conference | 978-1-6654-1236-0 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lijian Wei | 1 | 0 | 0.34 |
| Jun Feng | 2 | 44 | 16.44 |
| Yufei Liu | 3 | 0 | 0.34 |
| Tuo Zhang | 4 | 0 | 0.34 |
| Qirong Bu | 5 | 0 | 1.69 |
| Baoying Liu | 6 | 1 | 3.72 |