Search Results - "Reischl, Markus"

Image-based identification of optical quality and functional properties in inkjet-printed electronics using machine learning.

Authors: Polomoshnov, Maxim Reichert, Klaus-Martin Rettenberger, Luca et al.

Source: Journal of Intelligent Manufacturing; Apr2025, Vol. 36 Issue 4, p2709-2726, 18p

Assessment of a Fine-Tuned Vision-Language-Action Model for Robotic Feature-Following Inspection.

Authors: Krüger, Martin Salem, Mahmoud Reischl, Markus

Source: Neural Processing Letters; Jun2026, Vol. 58 Issue 3, p1-22, 22p

A review of adaptable conventional image processing pipelines and deep learning on limited datasets.

Authors: Münke, Friedrich Rieken Schützke, Jan Berens, Felix et al.

Source: Machine Vision & Applications; Mar2024, Vol. 35 Issue 2, p1-17, 17p

Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding.

Authors: Zhou, Baifan Pychynski, Tim Reischl, Markus et al.

Source: Journal of Intelligent Manufacturing; Apr2022, Vol. 33 Issue 4, p1139-1163, 25p

Leveraging unlabeled SEM datasets with self-supervised learning for enhanced particle segmentation.

Authors: Rettenberger, Luca Szymanski, Nathan J. Giunto, Andrea et al.

Source: NPJ Computational Materials; 9/22/2025, Vol. 11 Issue 1, p1-12, 12p

Bayesian Optimization Driven Cancer Drug Dose-Response Curve Discovery.

Authors: Höfer, Hawo H. Urrutia Gómez, Joaquín E. Popova, Anna A. et al.

Source: Current Directions in Biomedical Engineering; Sep2025, Vol. 11 Issue 1, p358-361, 4p

Automatic Labeling of Multi-Modal Sensor Training Data for Hand Gesture Analysis.

Authors: Hetto, Tom Reischl, Markus

Source: Current Directions in Biomedical Engineering; Sep2025, Vol. 11 Issue 1, p314-317, 4p

ML-Driven Contamination Classification for XPS Analysis of PLA Surfaces.

Authors: Orth, André Höfer, Hawo H. Wildersinn, Leonie et al.

Source: Current Directions in Biomedical Engineering; Sep2025, Vol. 11 Issue 1, p330-333, 4p

A novel metric for 6D pose estimation: Addressing errors and false detections for more reliable evaluation.

Authors: Niedermaier, Tobias Berens, Felix Reischl, Markus et al.

Source: Automatisierungstechnik; Feb2025, Vol. 73 Issue 2, p125-135, 11p

Highly Parallel and High‐Throughput Nanoliter‐Scale Liquid, Cell, and Spheroid Manipulation on Droplet Microarray.

Authors: Urrutia Gómez, Joaquin E. Zhou, Meijun Mandsberg, Nikolaj K. et al.

Source: Advanced Functional Materials; 1/2/2025, Vol. 35 Issue 1, p1-15, 15p

Adaptable Accelerometer Signal Processing Pipelines for Smartphone based Evenness Estimation.

Authors: Münke, Friedrich Rieken Schenk, Manuel Murr, Sandra et al.

Source: Journal of Signal Processing Systems for Signal, Image & Video Technology; Oct2024, Vol. 96 Issue 10, p617-626, 10p

Uncertainty-aware particle segmentation for electron microscopy at varied length scales.

Authors: Rettenberger, Luca Szymanski, Nathan J. Zeng, Yan et al.

Source: NPJ Computational Materials; 6/12/2024, Vol. 10 Issue 1, p1-9, 9p

Accelerating Materials Discovery: Automated Identification of Prospects from X‐Ray Diffraction Data in Fast Screening Experiments.

Authors: Schuetzke, Jan Schweidler, Simon Muenke, Friedrich R. et al.

Source: Advanced Intelligent Systems (2640-4567); Mar2024, Vol. 6 Issue 3, p1-9, 9p

A fully automated touch-response behavior inspection pipeline on zebrafish larvae.

Authors: Wang, Yanke Pylatiuk, Christian Mikut, Ralf et al.

Source: Automatisierungstechnik; Oct2023, Vol. 71 Issue 10, p845-852, 8p

Validating neural networks for spectroscopic classification on a universal synthetic dataset.

Authors: Schuetzke, Jan Szymanski, Nathan J. Reischl, Markus

Source: NPJ Computational Materials; 6/5/2023, Vol. 9 Issue 1, p1-12, 12p

An Automated Experimentation System for the Touch-Response Quantification of Zebrafish Larvae.

Authors: Wang, Yanke Marcato, Daniel Tirumalasetty, Vani et al.

Source: IEEE Transactions on Automation Science & Engineering; Oct2022, Vol. 19 Issue 4, p3007-3019, 13p

Evaluierung von Merkmalen zur Abbildung von Veränderungen in ungeordneten Bilddaten. (German)

Authors: Münke, Friedrich R. Schilling, Marcel P. Mikut, Ralf et al.

Source: Automatisierungstechnik; Oct2021, Vol. 69 Issue 10, p892-902, 11p

CAD-to-real: enabling deep neural networks for 3D pose estimation of electronic control units: A transferable and automated approach for industrial use cases.

Authors: Bäuerle, Simon Böhland, Moritz Barth, Jonas et al.

Source: Automatisierungstechnik; Oct2021, Vol. 69 Issue 10, p880-891, 12p

Motion prediction enables simulated MR-imaging of freely moving model organisms.

Authors: Reischl, Markus Jouda, Mazin MacKinnon, Neil et al.

Source: PLoS Computational Biology. 12/19/2019, Vol. 15 Issue 12, pN.PAG-N.PAG. 1p. 1 Color Photograph, 2 Black and White Photographs, 3 Diagrams, 2 Graphs.

A novel approach to label road defects in video data: semi-automated video analysis.

Authors: Thumm, Jakob Masino, Johannes Knoche, Martin et al.

Source: International Journal on Smart Sensing & Intelligent Systems; 2020, Vol. 13 Issue 1, p1-9, 9p