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kopuklu2020drivermhg

Titel:: DriverMHG: A Multi-Modal Dataset for Dynamic Recognition of Driver Micro Hand Gestures and a Real-Time Recognition Framework
Dokumenttyp:: Konferenzbeitrag
Autor(en):: Köpüklü, Okan; Ledwon, Thomas; Rong, Yao; Köse, Neslihan; Rigoll, Gerhard
Kongress- / Buchtitel:: 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)
Jahr:: 2020
Monat:: Nov
Seiten:: pp--275
BibTeX

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mediaTUM Gesamtbestand Einrichtungen Schools TUM School of Computation, Information and Technology Departments Computer Engineering Mensch-Maschine-Kommunikation (Prof. Rigoll)Author Köpüklü

mediaTUM Gesamtbestand Hochschulbibliographie 2020 Fakultäten Elektrotechnik und Informationstechnik Mensch-Maschine-Kommunikation (Prof. Rigoll)

mediaTUM Gesamtbestand Einrichtungen Schools TUM School of Computation, Information and Technology Departments Computer Engineering Mensch-Maschine-Kommunikation (Prof. Rigoll)Publication Year 2020

mediaTUM Gesamtbestand Einrichtungen Schools TUM School of Computation, Information and Technology Departments Computer Engineering Mensch-Maschine-Kommunikation (Prof. Rigoll)Author Rigoll

mediaTUM Gesamtbestand Einrichtungen Schools TUM School of Computation, Information and Technology Departments Computer Engineering Mensch-Maschine-Kommunikation (Prof. Rigoll)Author Köse