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Sebastian Meister
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Investigations on Explainable Artificial Intelligence methods for the deep learning classification of fibre layup defect in the automated composite manufacturing
S Meister, M Wermes, J Stüve, RM Groves
Composites Part B: Engineering 224, 109160, 2021
462021
Synthetic image data augmentation for fibre layup inspection processes: Techniques to enhance the data set
S Meister, N Möller, J Stüve, RM Groves
Journal of Intelligent Manufacturing 32 (6), 1767-1789, 2021
462021
Review of image segmentation techniques for layup defect detection in the Automated Fiber Placement process
RMG Sebastian Meister, Mahdieu A. M. Wermes, Jan Stüve
Journal of Intelligent Manufacturing, 2021
37*2021
Cross-evaluation of a parallel operating SVM–CNN classifier for reliable internal decision-making processes in composite inspection
S Meister, M Wermes, J Stueve, RM Groves
Journal of Manufacturing Systems 60, 620-639, 2021
192021
Automated, quality assured and high volume oriented production of fiber metal laminates (FML) for the next generation of passenger aircraft fuselage shells
H Ucan, J Scheller, C Nguyen, D Nieberl, T Beumler, A Haschenburger, ...
Science and Engineering of Composite Materials 26 (1), 502-508, 2019
162019
Algorithm assessment for layup defect segmentation from laser line scan sensor based image data
S Meister, MAM Wermes, J Stüve, RM Groves
Sensors and smart structures technologies for civil, mechanical, and …, 2020
132020
Imaging sensor data modelling and evaluation based on optical composite characteristics: Investigation of data quality for inline inspection
S Meister, L Grundhöfer, J Stüve, RM Groves
The International Journal of Advanced Manufacturing Technology 116 (11 …, 2021
72021
Performance evaluation of CNN and R-CNN based line by line analysis algorithms for fibre placement defect classification
S Meister, M Wermes
Production Engineering 17 (3), 391-406, 2023
62023
Reflectivity and emissivity analysis of thermoplastic CFRP for optimising Xenon heating and thermographic measurements
S Meister, A Kolbe, RM Groves
Composites Part A: Applied Science and Manufacturing 158, 106972, 2022
52022
Automated defect analysis using optical sensing and explainable artificial intelligence for fibre layup processes in composite manufacturing
S Meister
Delft University of Technology, 2022
52022
Explainability of deep learning classifier decisions for optical detection of manufacturing defects in the automated fiber placement process
S Meister, MAM Wermes, J Stüve, RM Groves
Automated Visual Inspection and Machine Vision IV 11787, 31-37, 2021
52021
Verfahren der INLINE-Qualitätssicherung und der zerstörungsfreien Prüfung innerhalb der Fertigungslinie von Faser-Metall-Laminaten
H Apmann, M Mayer, K Fortkamp, A Haschenburger, C Krombholz, ...
Deutsche Gesellschaft für Luft-und Raumfahrt-Lilienthal-Oberth eV, 2017
42017
Optical material characterisation of prepreg CFRP for improved composite inspection
S Meister, J Stüve, RM Groves
Applied Composite Materials 29 (2), 871-887, 2022
32022
Enhancements of an inline QA system for fiber layup processes
S Meister, S Kaestner, C Krombholz
22018
Konzeptionierung und Implementierung einer bildbasierten online-Qualitätssicherung für den automatisierten Faserlegeprozess
S Meister, C Krombholz
22017
Software for inline quality assurance within automated fibre layup processes
S Meister
12018
Ressourceneffizientes Fliegen durch intelligente Qualitätssicherung im Fertigungsprozess
S Meister, C Brauer
Bitkom Roundtable Digitale Luftfahrt, 2022
2022
Mit künstlicher Intelligenz den Fehlern auf der Spur
S Meister
2021
Erklärbarkeit von Entscheidungsprozessen Maschineller Lernverfahren am Beispiel der optischen Inspektion im Faserverbundleichtbau
J Brüst, S Meister, C Brauer
Fachhochschule Wedel, 2021
2021
Erklärbarkeit und Transparenz maschineller Entscheidungsprozesse zur Performancesteigerung bildbasierter Inspektionsprozesse im automatisierten Faserverbundleichtbau
M Wermes, S Meister
2021
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Articles 1–20