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A deep learning approach for the classification task of gravure printed patterns

Brumm, Pauline ; Lindner, Nils ; Weber, Tim Eike ; Sauer, Hans Martin ; Dörsam, Edgar (2021)
A deep learning approach for the classification task of gravure printed patterns.
doi: 10.14622/Advances_47_2021
Conference or Workshop Item, Bibliographie

Item Type: Conference or Workshop Item
Erschienen: 2021
Creators: Brumm, Pauline ; Lindner, Nils ; Weber, Tim Eike ; Sauer, Hans Martin ; Dörsam, Edgar
Type of entry: Bibliographie
Title: A deep learning approach for the classification task of gravure printed patterns
Language: English
Date: September 2021
Place of Publication: Athens, Greece
Book Title: Advances in Printing and Media Technology - Proceedings of the 47th International Research Conference of iarigai : Athens, Greece, 19–23 September 2021
DOI: 10.14622/Advances_47_2021
URL / URN: http://jpmtr.org/Advances_Vol_472021_online.pdf
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Printing Science and Technology (IDD)
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1194: Interaction between Transport and Wetting Processes
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1194: Interaction between Transport and Wetting Processes > Research Area C: New and Improved Applications
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1194: Interaction between Transport and Wetting Processes > Research Area C: New and Improved Applications > C01: Forced Wetting with Hydrodynamic Assist on Gravure Print Cylinders
Date Deposited: 20 Jan 2022 06:35
Last Modified: 20 Jan 2022 06:35
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