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

1 Citation (Scopus)

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

Bibliographical note

Funding Information:
This work was supported by IITP (2017-0-00418) and the Rohde & Schwarz for test instruments.

All Science Journal Classification (ASJC) codes

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

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