A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling

Jungwoon Park, Junyoung Jang, Geunhaeng Lee, Hyunmin Koh, Changhwan Kim, Tae Wook Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publication2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers
PublisherInstitute of Electrical and Electronics Engineers Inc.
PagesC24-C25
ISBN (Electronic)9784863487185
DOIs
Publication statusPublished - 2019 Jun
Event33rd Symposium on VLSI Circuits, VLSI Circuits 2019 - Kyoto, Japan
Duration: 2019 Jun 92019 Jun 14

Publication series

NameIEEE Symposium on VLSI Circuits, Digest of Technical Papers
Volume2019-June

Conference

Conference33rd Symposium on VLSI Circuits, VLSI Circuits 2019
CountryJapan
CityKyoto
Period19/6/919/6/14

Fingerprint

Gesture recognition
End effectors
Artificial intelligence
Radar
Sampling

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

Cite this

Park, J., Jang, J., Lee, G., Koh, H., Kim, C., & Kim, T. W. (2019). A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling. In 2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers (pp. C24-C25). [8777995] (IEEE Symposium on VLSI Circuits, Digest of Technical Papers; Vol. 2019-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/VLSIC.2019.8777995
Park, Jungwoon ; Jang, Junyoung ; Lee, Geunhaeng ; Koh, Hyunmin ; Kim, Changhwan ; Kim, Tae Wook. / A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling. 2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers. Institute of Electrical and Electronics Engineers Inc., 2019. pp. C24-C25 (IEEE Symposium on VLSI Circuits, Digest of Technical Papers).
@inproceedings{ea32395a1f14487cb183ddd4b75c8ccf,
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.",
author = "Jungwoon Park and Junyoung Jang and Geunhaeng Lee and Hyunmin Koh and Changhwan Kim and Kim, {Tae Wook}",
year = "2019",
month = "6",
doi = "10.23919/VLSIC.2019.8777995",
language = "English",
series = "IEEE Symposium on VLSI Circuits, Digest of Technical Papers",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "C24--C25",
booktitle = "2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers",
address = "United States",

}

Park, J, Jang, J, Lee, G, Koh, H, Kim, C & Kim, TW 2019, A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling. in 2019 Symposium on VLSI Circuits, VLSI Circuits 2019 - Digest of Technical Papers., 8777995, IEEE Symposium on VLSI Circuits, Digest of Technical Papers, vol. 2019-June, Institute of Electrical and Electronics Engineers Inc., pp. C24-C25, 33rd Symposium on VLSI Circuits, VLSI Circuits 2019, Kyoto, Japan, 19/6/9. https://doi.org/10.23919/VLSIC.2019.8777995

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 proceedingConference 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 -

Park J, Jang J, Lee G, Koh H, Kim C, Kim TW. A Time Domain Artificial Intelligence Radar for Hand Gesture Recognition Using 33-GHz Direct Sampling. In 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). https://doi.org/10.23919/VLSIC.2019.8777995