24 GHz FMCW Radar System for Real-Time Hand Gesture Recognition Using LSTM

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dc.contributor.authorSuh, Junseukko
dc.contributor.authorRyu, Si Jungko
dc.contributor.authorHan, Byunghunko
dc.contributor.authorChoi, JaeWooko
dc.contributor.authorKim, Jong-Hwanko
dc.contributor.authorHong, Songcheolko
dc.date.accessioned2020-12-01T23:30:23Z-
dc.date.available2020-12-01T23:30:23Z-
dc.date.created2020-12-01-
dc.date.issued2018-11-08-
dc.identifier.citation30th Asia-Pacific Microwave Conference, APMC 2018, pp.860 - 862-
dc.identifier.urihttp://hdl.handle.net/10203/277883-
dc.description.abstractA 24 GHz frequency modulated continuous wave radar system to recognize human's hand gestures is implemented, which uses commercial off-the-shelf RF front-end IC with one transmitter and four receivers. Planar patch array antennas, signal conditioning circuits and interconnections to a PC are designed for the system. Range-Doppler maps for four receiver channels are obtained with saw-tooth chirping signals transmitted to detect hand gestures. The radar system shows real-time highly accurate gesture recognition. Long-short term memory recurrent neural network as a supervised machine learning technique is used. Seven kinds of hand gestures are recognized within 0.4 m and ±30° from the center of the transmitted antenna with above 91 % accuracy.-
dc.languageEnglish-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.title24 GHz FMCW Radar System for Real-Time Hand Gesture Recognition Using LSTM-
dc.typeConference-
dc.identifier.wosid000457599800283-
dc.identifier.scopusid2-s2.0-85061768080-
dc.type.rimsCONF-
dc.citation.beginningpage860-
dc.citation.endingpage862-
dc.citation.publicationname30th Asia-Pacific Microwave Conference, APMC 2018-
dc.identifier.conferencecountryJA-
dc.identifier.conferencelocationKyoto-
dc.identifier.doi10.23919/APMC.2018.8617375-
dc.contributor.localauthorKim, Jong-Hwan-
dc.contributor.localauthorHong, Songcheol-
dc.contributor.nonIdAuthorHan, Byunghun-
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EE-Conference Papers(학술회의논문)
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