Veröffentlichungen

• Schorr, C.; Luschkova, M.; Dahmen, T.: Automatic detection of billets in rolling mills using convolutional neural networks with synthetic data,  In: International Conference on NDE 4.0, Berlin,  2022
• Allweyer O., Schorr C., Mohr A., Krieger R.: Product Classification Using Partially Abbreviated Product Names, Brands and Dimensions,  In: Data Management Technologies and Applications. DATA 2020. Communications in Computer and Information Science,  Vol. 1446,  DOI  10.1007/978-3-030-83014-4_11,  2021
• Schorr, C.; Goodarzi, P.; Chen, F.; Dahmen, T.: Neuroscope - An explainable AI toolbox for semantic segmentation and classification of deep neural nets,  In: Applied Science, special issue on explainable AI,  Vol. 11,  Nr. 5,  DOI  10.3390/app11052199,  2021
• Schorr, C.: Hybrid consistency and plausibility verification of product data according to the EU regulation on food information to consumers (FIC),  arXiv:2102.02665,  2021
• Fritsch, T.; Schorr, C.: CT-Reihenanalyse spätlatènezeitlicher, eiserner Dosen und Kapseln aus Rheinhessen und dem Hunsrück - Fertigungstechnische Details als Chance der Erkennung von Werkstätten?,,  In: Archäologie in Rheinhessen und Umgebung,  Vol. 13,  S. 39-69,  2020
• Schorr, C.: Machine Learning assisted Alcoholic Beverage Classification for Retail,  In: Proceedings of the Upper-Rhine Artificial Intelligence Symposium 2020,  S. 12-23,  2020
• Allweyer, O.; Schorr, C.; Krieger, R.; Mohr, A.: Product classification based on partially abbreviated product names in retail,  In: 9th International Conference on Data Science, Technology and Applications (DATA), Paris, France,  2020
• Harth, M.; Schorr, C.; Krieger, R.: A hierarchical multi-level product classification workbench for retail,  In: Learning, Knowledge, Data, Analytics Conference, Bonn,  2020
• Schorr, C.; Krieger, R.: A Reference Model for Product Data Profiling in Retail ERP Systems,  In: 8th International Conference on Data Science, Technology and Applications (DATA), Prague, Czech Republic,  2019
• Vogelgesang, J.; Schorr, C.: Iterative Region-of-interest Reconstruction using Priori Information,  In: Sens Imaging,  Vol. 18,  Nr. 16,  DOI  10.1007/s11220-017-0165-8,  2017
• Trampert, P.; Vogelgesang, J.; Schorr, C.; Maisl, M.; Bogachev, S.; Marniok, N. et al.: Spherically Symmetric Volume Elements as Basis Functions for Reconstructions in Computed Laminography,  In: Journal of X-Ray Science and Technology,  Vol. 25,  Nr. 4,  S. 533-546,  DOI  10.3233/XST-16230,  2017
• Dörr, L.; Maisl, M.; Schorr, C.; Schuster, T.: Registration of a priori Information for Computed Laminography,  In: , NDT&E International,  Vol. 106,  S. 106-112,  DOI  10.22028/D291-28324,  2017
• Vogelgesang, J.; Schorr, C.: A Semi-Discrete Landweber–Kaczmarz Method for Cone Beam Tomography and Laminography Exploiting Geometric Prior Information,  In: Sens Imaging,  Vol. 17,  Nr. 17,  DOI  10.1007/s11220-016-0142-7,  2017
• Dörr, L.; Maisl, M.; Schorr, C.: Advanced computed laminography using a priori information,  In: Proceedings of the 19th World Conference on Non-Destructive Testing 2016, Munich,  2016
• Maisl, M.; Scholl, H.; Schorr, C.; Seemann, R.: Reconstruction of fluid flows in porous media using geometric a priori information,  In: Review of Scientific Instruments,  Vol. 87,  Nr. 12,  DOI  10.1063/1.4971301,  2016
• Dörr, L.; Maisl, M.; Schorr, C.: Applying a priori Information to computed laminography,  In: Proceedings of the Digital Industrial Radiology and Computed Tomography (DIR 2015), Ghent, Belgium,  2015
• Fritsch, T.; Schorr, C.: Röntgenanalyse der Pyxis von Bierfeld, Gde. Nonnweiler, Flur “Vor dem Erker”, Fst. 5,  In: Bull. Soc. Préhist. Luxembourgeoise,  Vol. 36,  S. 219-224,  2015
• Dörr, L.; Maisl, M.; Schorr, C.: Semi-automatische Registrierung von a priori Modellen und Messdaten für die Computertomographie und -laminographie,  In: Proceedings DACH-Jahrestagung 2015, Salzburg, Austria,  2015