| Machine learning as a comparative tool to determine the relevance of signal features in laser welding C Knaak, U Thombansen, P Abels, M Kröger Procedia CIRP 74, 623-627, 2018 | 55 | 2018 |
| Improving build quality in laser powder bed fusion using high dynamic range imaging and model-based reinforcement learning C Knaak, L Masseling, E Duong, P Abels, A Gillner IEEE access 9, 55214-55231, 2021 | 54 | 2021 |
| A spatio-temporal ensemble deep learning architecture for real-time defect detection during laser welding on low power embedded computing boards C Knaak, J von Eßen, M Kröger, F Schulze, P Abels, A Gillner Sensors 21 (12), 4205, 2021 | 51 | 2021 |
| Deep learning-based semantic segmentation for in-process monitoring in laser welding applications C Knaak, G Kolter, F Schulze, M Kröger, P Abels Applications of machine learning 11139, 10-22, 2019 | 43 | 2019 |
| Monitoring of the powder bed quality in metal additive manufacturing using deep transfer learning FG Fischer, MG Zimmermann, N Praetzsch, C Knaak Materials & Design 222, 111029, 2022 | 41 | 2022 |
| Scan path resolved thermal modelling of LPBF E Duong, L Masseling, C Knaak, P Dionne, M Megahed Additive Manufacturing Letters 3, 100047, 2022 | 20 | 2022 |
| Uncooled MWIR PbSe technology outperforms CMOS in RT closed-loop control and monitoring of laser processing J Rodríguez-Araújo, A Garcia-Diaz, V Panadeiro, C Knaak Applied industrial optics: Spectroscopy, imaging and metrology, ATh2A. 2, 2017 | 13 | 2017 |
| Deep learning and conventional machine learning for image-based in-situ fault detection during laser welding: A compara-tive study C Knaak, M Kröger, F Schulze, P Abels, A Gillner Engineering 21 (12), 4205, 2021 | 3 | 2021 |
| Datennutzung und Datenreduktion in der Lasermaterialbearbeitung: Lernen aus der vollständigen Information U Thombansen, P Abels, W Fiedler, C Knaak, M Kröger, A Lanfermann, ... Monetarisierung von technischen Daten: Innovationen aus Industrie und …, 2021 | 2 | 2021 |
| AI-based quality monitoring of auto-body weld joints in real time: Christian Knaak and Peter Abels, of Fraunhofer ILT, explain how imaging and machine learning can be used to … C Knaak, P Abels Laser Systems Europe, 12-14, 2020 | 1 | 2020 |
| AI-driven autonomous adaptative feedback welding machine B von Querfurth, SE Belhout, C Knaak, S Mann, P Abels, C Holly, ... Welding in the World, 1-8, 2025 | | 2025 |
| Development and Commercialization of Adaptive Feedback Welding Technology for Fabrication and Repair Applications SE Belhout, J Tatman, D Barborak, M Hargadine, B von Querfurth, ... Advances in Materials Technology for Power Plants 84871, 50-61, 2024 | | 2024 |
| Process Monitoring and Control P Abels, C Knaak, K Kowalick, S Kaierle, A Lanfermann, B Regaard Tailored Light 2: Laser Applications, 747-784, 2023 | | 2023 |
| Data Utilization and Data Reduction in Laser Material Processing: Learning From the Complete Information U Thombansen, P Abels, W Fiedler, C Knaak, M Kröger, A Lanfermann, ... The Monetization of Technical Data: Innovations from Industry and Research …, 2023 | | 2023 |
| Defect localization during laser microwelding of battery connectors using long exposure imaging and few-shot learning C Knaak, BE von Querfurth, S Hollatz, E Duong, P Abels, A Olowinsky Procedia CIRP 111, 790-795, 2022 | | 2022 |
| Identifikation von Prozessfehlern C Knaak, P Abels Qualität und Zuverlässigkeit: QZ, 2020 | | 2020 |
| Characterisation of the optical emisson in laser powder bed fusion process E Duong, M Kröger, U Thombansen, C Knaak, P Abels International Congress on Laser Advanced Materials Processing (LAMP) 2019, 2019 | | 2019 |
Antón Garcia-DiazFounder at Abraia SoftwareVerified email at abraiasoftware.com
