End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB

^*Korrespondierende/r Autor/-in für diese Arbeit

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

Originalsprache	englisch
Titel	2021 IEEE International Conference on Robotics and Automation (ICRA)
Seiten	13452 - 13458
Seitenumfang	7
Publikationsstatus	Veröffentlicht - 2021
Veranstaltung	2021 IEEE International Conference on Robotics and Automation: IEEE ICRA 2021 - Xi'an, Hybrider Event, China Dauer: 31 Mai 2021 → 4 Juni 2021

Konferenz	2021 IEEE International Conference on Robotics and Automation
Kurztitel	ICRA 2021
Land/Gebiet	China
Ort	Hybrider Event
Zeitraum	31/05/21 → 4/06/21

End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB
Stefan Ainetter (Redner/in)
3 Juni 2021
Aktivität: Vortrag oder Präsentation › Vortrag bei Konferenz oder Fachtagung › Science to science

Dieses zitieren

@inproceedings{1a103f5e5beb4de19b5ae1a883b60a02,

title = "End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB",

author = "Stefan Ainetter and Friedrich Fraundorfer",

year = "2021",

language = "English",

pages = "13452 -- 13458",

booktitle = "2021 IEEE International Conference on Robotics and Automation (ICRA)",

note = "2021 IEEE International Conference on Robotics and Automation : IEEE ICRA 2021, ICRA 2021 ; Conference date: 31-05-2021 Through 04-06-2021",

}

TY - GEN

T1 - End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB

AU - Ainetter, Stefan

AU - Fraundorfer, Friedrich

PY - 2021

Y1 - 2021

M3 - Conference paper

SP - 13452

EP - 13458

BT - 2021 IEEE International Conference on Robotics and Automation (ICRA)

T2 - 2021 IEEE International Conference on Robotics and Automation

Y2 - 31 May 2021 through 4 June 2021

ER -