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Learning with Known Operators reduces Maximum Training Error Bounds.

A. Maier, C. Syben, B. Stimpel, T. Würfl, M. Hoffmann, F. Schebesch, W. Fu, L. Mill, L. Kling, and S. Christiansen. CoRR, (2019)

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Dr. rer. nat. Bernhard Schulz University of Stuttgart

Bernhard Schopfer University of Stuttgart

Prof. Dr. Bernhard Hauer University of Stuttgart

Hon. -Prof. Dr. Bernhard Scheuble University of Stuttgart

Univ. -Prof. Dr. -Ing. Bernhard Mitschang University of Stuttgart

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User Loss A Forced-Choice-Inspired Approach to Train Neural Networks Directly by User Interaction.S. Zarei, B. Stimpel, C. Syben, and A. Maier. Bildverarbeitung für die Medizin, page 92-97. Springer Vieweg, (2019)Projection image-to-image translation in hybrid x-ray/MR imaging.B. Stimpel, C. Syben, T. Würfl, K. Breininger, J. Lommen, A. Dörfler, and A. Maier. Medical Imaging: Image Processing, volume 10949 of SPIE Proceedings, page 109492K. SPIE, (2019)Abstract: Fan-to-Parallel Beam Conversion - Deriving Neural Network Architectures Using Precision Learning.C. Syben, B. Stimpel, J. Lommen, T. Würfl, A. Dörfler, and A. Maier. Bildverarbeitung für die Medizin, page 29. Springer Vieweg, (2019)Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging.B. Stimpel, C. Syben, T. Würfl, K. Breininger, P. Hoelter, A. Dörfler, and A. Maier. CoRR, (2019)Learning with Known Operators reduces Maximum Training Error Bounds.A. Maier, C. Syben, B. Stimpel, T. Würfl, M. Hoffmann, F. Schebesch, W. Fu, L. Mill, L. Kling, and S. Christiansen. CoRR, (2019)Projection image-to-image translation in hybrid X-ray/MR imaging.B. Stimpel, C. Syben, T. Würfl, K. Breininger, K. Mentl, J. Lommen, A. Dörfler, and A. Maier. CoRR, (2018)User Loss - A Forced-Choice-Inspired Approach to Train Neural Networks directly by User Interaction.S. Zarei, B. Stimpel, C. Syben, and A. Maier. CoRR, (2018)Automated Curved and Multiplanar Reformation for Screening of the Proximal Coronary Arteries in MR Angiography.B. Stimpel, J. Wetzl, C. Forman, M. Schmidt, A. Maier, and M. Unberath. J. Imaging, 4 (11): 124 (2018)A Deep Learning Approach for Reconstruction Filter Kernel Discretization.C. Syben, B. Stimpel, K. Breininger, T. Würfl, R. Fahrig, A. Dörfler, and A. Maier. CoRR, (2017)Maximum Likelihood Estimation of Head Motion Using Epipolar Consistency.A. Preuhs, N. Ravikumar, M. Manhart, B. Stimpel, E. Hoppe, C. Syben, M. Kowarschik, and A. Maier. Bildverarbeitung für die Medizin, page 134-139. Springer Vieweg, (2019)

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Learning with Known Operators reduces Maximum Training Error Bounds.

Please choose a person to relate this publication to

Dr. rer. nat. Bernhard Schulz University of Stuttgart

Bernhard Schopfer University of Stuttgart

Prof. Dr. Bernhard Hauer University of Stuttgart

Hon. -Prof. Dr. Bernhard Scheuble University of Stuttgart

Univ. -Prof. Dr. -Ing. Bernhard Mitschang University of Stuttgart

Other publications of authors with the same name

Disambiguation

PUMA

Disambiguation of "Stimpel, Bernhard"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Learning with Known Operators reduces Maximum Training Error Bounds.

Please choose a person to relate this publication to

Dr. rer. nat. Bernhard Schulz University of Stuttgart

Bernhard Schopfer University of Stuttgart

Prof. Dr. Bernhard Hauer University of Stuttgart

Hon. -Prof. Dr. Bernhard Scheuble University of Stuttgart

Univ. -Prof. Dr. -Ing. Bernhard Mitschang University of Stuttgart

Other publications of authors with the same name

Disambiguation

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URL
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Learning with Known Operators reduces Maximum Training Error Bounds.