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.
| Original language | English |
|---|---|
| Title of host publication | 2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | C24-C25 |
| ISBN (Electronic) | 9784863487185 |
| DOIs | |
| Publication status | Published - 2019 Jun |
| Event | 33rd Symposium on VLSI Circuits, VLSI Circuits 2019 - Kyoto, Japan Duration: 2019 Jun 9 → 2019 Jun 14 |
Publication series
| Name | IEEE Symposium on VLSI Circuits, Digest of Technical Papers |
|---|---|
| Volume | 2019-June |
Conference
| Conference | 33rd Symposium on VLSI Circuits, VLSI Circuits 2019 |
|---|---|
| Country | Japan |
| City | Kyoto |
| Period | 19/6/9 → 19/6/14 |
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All Science Journal Classification (ASJC) codes
- Electronic, Optical and Magnetic Materials
- Electrical and Electronic Engineering
Cite this
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A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling. / Park, Jungwoon; Jang, Junyoung; Lee, Geunhaeng; Koh, Hyunmin; Kim, Changhwan; Kim, Tae Wook.
2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers. Institute of Electrical and Electronics Engineers Inc., 2019. p. C24-C25 8777995 (IEEE Symposium on VLSI Circuits, Digest of Technical Papers; Vol. 2019-June).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling
AU - Park, Jungwoon
AU - Jang, Junyoung
AU - Lee, Geunhaeng
AU - Koh, Hyunmin
AU - Kim, Changhwan
AU - Kim, Tae Wook
PY - 2019/6
Y1 - 2019/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85073907873&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073907873&partnerID=8YFLogxK
U2 - 10.23919/VLSIC.2019.8777995
DO - 10.23919/VLSIC.2019.8777995
M3 - Conference contribution
AN - SCOPUS:85073907873
T3 - IEEE Symposium on VLSI Circuits, Digest of Technical Papers
SP - C24-C25
BT - 2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers
PB - Institute of Electrical and Electronics Engineers Inc.
ER -