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Volumn 2015-December, Issue , 2015, Pages 4415-4420

Generating multi-fingered robotic grasps via deep learning

Author keywords

Computer architecture; Grasping; Heating; Image segmentation; Machine learning; Training; Training data

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER ARCHITECTURE; HEATING; IMAGE SEGMENTATION; LEARNING SYSTEMS; PERSONNEL TRAINING;

EID: 84958167103     PISSN: 21530858     EISSN: 21530866     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2015.7354004     Document Type: Conference Paper
Times cited : (145)

References (19)
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    • Lenz, I.1    Lee, H.2    Saxena, A.3
  • 13
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    • Yun Lin and Yu Sun. Robot grasp planning based on demonstrated grasp strategies. The International Journal of Robotics Research, 34(1):26-42, 2015.
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    • Lin, Y.1    Sun, Y.2
  • 14
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    • Graspit! a versatile simulator for robotic grasping
    • Andrew T Miller and Peter K Allen. Graspit! a versatile simulator for robotic grasping. Robotics & Automation Magazine, IEEE, 11(4):110-122, 2004.
    • (2004) Robotics & Automation Magazine, IEEE , vol.11 , Issue.4 , pp. 110-122
    • Miller, A.T.1    Allen, P.K.2
  • 17
    • 84906908634 scopus 로고    scopus 로고
    • Semantic 3D object maps for everyday manipulation in human living environments
    • Radu Bogdan Rusu. Semantic 3D object maps for everyday manipulation in human living environments. KI-Künstliche Intelligenz, 24(4):345-348, 2010.
    • (2010) KI-Künstliche Intelligenz , vol.24 , Issue.4 , pp. 345-348
    • Bogdan Rusu, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.