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Machine Vision Competence as a Function of Computing Power -- Four Years Later

Hans-Hellmut Nagel 1, 2 Thomas Muller 1 Volker Gengenbach 2 Nicolas Andreff 3 Alexander Bachem 1 Radu Horaud 3 H. Leuck 1
3 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : Annual increases in workstation capacity suggest that today between 5 and 15 times the computing power of 1994 should be available in a laboratory. We discuss the consequences for the specific case of robot control by real-time machine vision in an automatic disassembly cell, characterizing machine vision competence by speed, robustness, versatility, analyzability, and maintainability.
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https://hal.inria.fr/inria-00590097
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Submitted on : Tuesday, May 3, 2011 - 9:19:20 AM
Last modification on : Tuesday, October 19, 2021 - 12:49:45 PM
Long-term archiving on: : Thursday, August 4, 2011 - 2:53:53 AM

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  • HAL Id : inria-00590097, version 1

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Hans-Hellmut Nagel, Thomas Muller, Volker Gengenbach, Nicolas Andreff, Alexander Bachem, et al.. Machine Vision Competence as a Function of Computing Power -- Four Years Later. IAR Annual Report 1998, IAR, French-German Institute for Research Applications, 1998, undef, Samoa. pp.15--22. ⟨inria-00590097⟩

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