SES-05: Deep Learning-based Inspection

  • Single-Shot X-ray to Multi-View Projections for 3D Pork Shoulder Bone Analysis

Michiel Pieters1, Pieter Verboven1, Bart Nicolaï1,2

1Ku Leuven, Belgium; 2Flanders Centre of Postharvest Technology,Belgium


  • Superimposing Synthetic Defects into Real CT Scans for Advanced Probability of Detection Evaluation

Miroslav Yosifov1,2, Bernhard Fröhler1, Jan De Beenhouwer2, Jan Sijbers2, Johann Kastner1, Christoph Heinzl3,4

1University of Applied Sciences Upper Austria, Wels, Austria; 2imec-Vision Lab, Dept. of Physics, University of Antwerp, Universiteitsplein 1, 2610 Antwerpen, Belgium; 3University of Passau, Innstraße 43, Passau, Germany; 4Fraunhofer Institute for Integrated Circuits IIS, Division Development Center X-ray Technology, Flugplatzstraße 75, Fürth, Germany


  • Combining Deep Learning and scatterControl for High-Throughput X-ray CT based Non-Destructive Characterization of Large-Scale Casted Metallic Components

Amir Koushyar Ziabari1, Mohamed Hakim Bedhief2, Obaidullah Rahman1, Singanallur Venkatakrishnan1, Paul Brackman3, Peter Katuch2

1Oak Ridge National Lab, United States of America; 2Carl ZEISS IMT GmbH; 3ZEISS Industrial Quality Solutions


  • Proximal Neural Networks based reconstruction for few-view CT applications

Hoang Trieu Vy LE1, C. Bossuyt2, J. Escoda1, M. Costin1, J. De Beenhouwer2, J. Sijbers2

1CEA, France; 2IMEC - Vision Lab, University of Antwerp, 2610 Antwerpen, Belgium