Name
Title | ||
|---|---|---|
A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling |
Abstract | ||
|---|---|---|
This research developed time domain Artificial Intelligence radar using up to 33 GS/s direct sampling technique. It can recognize both static and dynamic hand gesture by learning the unique impulse signal that comes back from target. The algorithm gets recognition rate 93.2% and 90.5%, respectively on set of static and dynamic gesture. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.23919/VLSIC.2019.8777995 | 2019 Symposium on VLSI Circuits |
Keywords | Field | DocType |
hand gesture recognition,direct sampling technique,static hand gesture,dynamic hand gesture,impulse signal,time domain artificial intelligence radar | Time domain,Radar,Gesture,Computer science,Gesture recognition,Impulse (physics),Direct sampling,Artificial intelligence | Conference |
ISSN | ISBN | Citations |
2158-5601 | 978-1-7281-0914-5 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jungwoon Park | 1 | 0 | 0.34 |
| Junyoung Jang | 2 | 0 | 0.34 |
| Geunhaeng Lee | 3 | 4 | 1.52 |
| Hyunmin Koh | 4 | 0 | 0.34 |
| ChangHwan Kim | 5 | 160 | 22.61 |
| Tae Wook Kim | 6 | 86 | 17.66 |