Frederic Schulze
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View article: A Spatio-Temporal Ensemble Deep Learning Architecture for Real-Time Defect Detection during Laser Welding on Low Power Embedded Computing Boards
A Spatio-Temporal Ensemble Deep Learning Architecture for Real-Time Defect Detection during Laser Welding on Low Power Embedded Computing Boards Open
In modern production environments, advanced and intelligent process monitoring strategies are required to enable an unambiguous diagnosis of the process situation and thus of the final component quality. In addition, the ability to recogni…
View article: Deep Learning and Conventional Machine Learning for Image-Based in-Situ Fault Detection During Laser Welding: A Comparative Study
Deep Learning and Conventional Machine Learning for Image-Based in-Situ Fault Detection During Laser Welding: A Comparative Study Open
An effective process monitoring strategy is a requirement for meeting the challenges posed by increasingly complex products and manufacturing processes. To address these needs, this study investigates a comprehensive scheme based on classi…
View article: Development of a flexible low laser power hybrid (LLPH) technology for shipbuilding including additive manufacturedsemi-automated hand-held unit
Development of a flexible low laser power hybrid (LLPH) technology for shipbuilding including additive manufacturedsemi-automated hand-held unit Open
A novel Low Laser Power Hybrid (LLPH) technology overcomes manufacturing gaps between 2D panels and 3D sections in shipbuilding. Construction, process, equipment and additive manufacturing knowledge are combined in the project “ShipLight”.…