Benjamin Lutz

Lehrstuhl für Fertigungsautomatisierung und Produktionssystematik (FAPS)

Interactive Image Segmentation Using Superpixels and Deep Metric Learning for Tool Condition Monitoring (2023) Lutz B, Janisch L, Kißkalt D, Regulin D, Franke J Conference contribution Towards Material-Batch-Aware Tool Condition Monitoring (2021) Lutz B, Howell P, Regulin D, Engelmann B, Franke J Journal article Automated Domain Adaptation in Tool Condition Monitoring using Generative Adversarial Networks (2021) Lutz B, Kißkalt D, Regulin D, Aybar B, Franke J Conference contribution Material identification for smart manufacturing systems: A review (2021) Lutz B, Kißkalt D, Regulin D, Hauser T, Franke J Conference contribution Porosity in wire arc additive manufacturing of aluminium alloys (2021) Hauser T, Reisch RT, Breese PP, Lutz B, Pantano M, Nalam Y, Bela K, et al. Journal article Semantic Segmentation of Multi-Channel Polycrystalline Structure Micrographs Using Convolutional Neural Networks (2021) Selmaier A, Lutz B, Kißkalt D, Boernicke S, Fuerst J, Franke J Conference contribution In-situ identification of material batches using machine learning for machining operations (2020) Lutz B, Kißkalt D, Mayr A, Regulin D, Pantano M, Franke J Journal article Distance-Based Multivariate Anomaly Detection in Wire Arc Additive Manufacturing (2020) Reisch R, Hauser T, Lutz B, Pantano M, Kamps T, Knoll A Conference contribution Benchmark of automated machine learning with state-of-the-art image segmentation algorithms for tool condition monitoring (2020) Lutz B, Reisch R, Kißkalt D, Avci B, Regulin D, Knoll A, Franke J Journal article, Original article AI-based approach for predicting the machinability under consideration of material batch deviations in turning processes (2020) Lutz B, Kißkalt D, Regulin D, Franke J Journal article