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College of Engineering(공과대학)School of Electrical Engineering(전기및전자공학부)EE-Conference Papers(학술회의논문)

DSPU: A 281.6mW Real-Time Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip

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dc.contributor.authorIm, DongSeokko
dc.contributor.authorPark, Gwangtaeko
dc.contributor.authorLi, Zhiyongko
dc.contributor.authorRyu, Junhako
dc.contributor.authorKang, Sanghoonko
dc.contributor.authorHan, Donghyeonko
dc.contributor.authorLee, Jinsuko
dc.contributor.authorPark, Wonhoonko
dc.contributor.authorKown, Hankyulko
dc.contributor.authorYoo, Hoi-Junko
dc.date.accessioned2023-01-12T10:01:48Z-
dc.date.available2023-01-12T10:01:48Z-
dc.date.created2023-01-09-
dc.date.issued2022-08-
dc.identifier.citation2022 IEEE Hot Chips 34 Symposium, HCS 2022-
dc.identifier.urihttp://hdl.handle.net/10203/304349-
dc.languageEnglish-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleDSPU: A 281.6mW Real-Time Deep Learning-Based Dense RGB-D Data Acquisition with Sensor Fusion and 3D Perception System-on-Chip-
dc.typeConference-
dc.identifier.scopusid2-s2.0-85140981529-
dc.type.rimsCONF-
dc.citation.publicationname2022 IEEE Hot Chips 34 Symposium, HCS 2022-
dc.identifier.conferencecountryUS-
dc.identifier.conferencelocationCupertino-
dc.identifier.doi10.1109/HCS55958.2022.9895605-
dc.contributor.localauthorYoo, Hoi-Jun-
dc.contributor.nonIdAuthorKang, Sanghoon-
dc.contributor.nonIdAuthorLee, Jinsu-
dc.contributor.nonIdAuthorPark, Wonhoon-
dc.contributor.nonIdAuthorKown, Hankyul-
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EE-Conference Papers(학술회의논문)
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