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Sheared edge defect segmentation using a convolutional U-Net for quantified quality assessment of fine blanked workpieces

Precision Engineering, vol. 75, pp. 129–141

Authors 4

  1. RWTH Aachen University

    Affiliation as printed

    Chair of Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

    Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

  2. RWTH Aachen University

    Affiliation as printed

    Chair of Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

    Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

  3. RWTH Aachen University

    Affiliation as printed

    Chair of Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

    Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

  4. RWTH Aachen University · Fraunhofer Institute for Production Technology IPT

    Affiliation as printed

    Chair of Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

    Fraunhofer Institute for Production Technology IPT, Germany

    Production Metrology and Quality Management of WZL | RWTH Aachen University, Campus Boulevard 30, Aachen, 52074, Germany

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References 45