Johannes C. Bauer

11 papers C 5Journal 4Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Handling data drift in deep learning-based quality monitoring: evaluating calibration methods using the example of friction stir welding.
J. Intell. Manuf.
Johannes C. Bauer, Stephan Trattnig, Fabian Vieltorf, Rüdiger Daub
2026 J jnl
Multi-Level Feature Fusion for Continual Learning in Visual Quality Inspection.
CoRR
Johannes C. Bauer, Paul Geng, Stephan Trattnig, Petr Dokládal, Rüdiger Daub
2025 C conf
A Dataset and Baseline for Deep Learning-Based Visual Quality Inspection in Remanufacturing.
ETFA
Johannes C. Bauer, Paul Geng, Stephan Trattnig, Petr Dokládal, Rüdiger Daub
2025 J jnl
A Dataset and Baseline for Deep Learning-Based Visual Quality Inspection in Remanufacturing.
CoRR
Johannes C. Bauer, Paul Geng, Stephan Trattnig, Petr Dokládal, Rüdiger Daub
2025 — conf
Digital Workpiece Model Creation for the Automated Configuration and Commissioning of Industrial Robotic Applications.
CASE
Paul Geng, Michael Jonas Pressnig, Johannes C. Bauer, Stephan Trattnig, Lukas Tanz, Rüdiger Daub
2025 C conf
Experimental Investigation on the Handling Stability of Vacuum Grippers with Multiple Suction Cups.
ETFA
Paul Geng, Sebastian Fendt, Stephan Trattnig, Johannes C. Bauer, Lukas Tanz, Rüdiger Daub
2025 C conf
Few-Shot Learning-Based Analysis of Production Areas Using Large Foundation Models and Metric Learning.
ETFA
Johannes C. Bauer, Johanna Dechent, Stephan Trattnig, Paul Geng, Sonja Wächter, Rüdiger Daub
2025 — conf
Multi-Level Feature Fusion for Continual Learning in Visual Quality Inspection.
ICCMA
Johannes C. Bauer, Paul Geng, Stephan Trattnig, Petr Dokládal, Rüdiger Daub
2024 C conf
Reliable Deep Learning-Based Analysis of Production Areas Using RGB-D Data and Model Confidence Calibration.
ETFA
Johannes C. Bauer, Kutay Yilmaz, Sonja Wächter, Rüdiger Daub
2023 C conf
Continuous Adaptation of Deep Learning Models for Optical Quality Monitoring Tasks.
ETFA
Johannes C. Bauer, Rüdiger Daub
2022 J jnl
An optimal-score-based filter pruning for deep convolutional neural networks.
Appl. Intell.
Shrutika S. Sawant, Johannes C. Bauer, F. X. Erick, Subodh Ingaleshwar, Nina Holzer, A. Ramming, Elmar W. Lang, Theresa Götz