Dr.-Ing

Oliver Rippel

Research Scientist

 139
 +49 241 80 27860
 lfb@lfb.rwth-aachen.de



Curriculum Vitae

Dec 2017 – Nov. 2022
Research Scientist, Institute of Imaging & Computer Vision, RWTH Aachen University, Germany
Oct 2015 – Nov 2017 M. Sc. Biomedical Engineering, RWTH Aachen University, Germany
Oct 2012 – Sep 2015 B. Sc. Molecular Biomedicine, Rheinische Friedrich-Wilhelms-University, Bonn, Germany

Research Field

Automated Defect Detection for Industrial Quality Control

Publications

2022

Rippel, Oliver Christoph Johannes
Vision-based open set recognition for industrial inspection systems

2022

Oliver Rippel, Corinna Zwinge and Dorit Merhof
Increasing the Generalization of Supervised Fabric Anomaly Detection Methods to Unseen Fabrics
In: Sensors 22 (13)

2022

Oliver Rippel, Nikolaj Schönfelder, Khosrow Rahimi, Juliana Kurniadi, Andreas Herrmann and Dorit Merhof
Panoptic Segmentation of Animal Fibers
In: 2022 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

2022

Oliver Rippel, Arnav Chavan, Chucai Lei and Dorit Merhof
Transfer Learning Gaussian Anomaly Detection by Fine-tuning Representations
In: Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE

2022

Oliver Rippel, Sergen Gülçelik, Khosrow Rahimi, Juliana Kurniadi, Andreas Herrmann and Dorit Merhof
Animal Fiber Identification under the Open Set Condition
In: 17th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP)

2021

Oliver Rippel, Patrick Mertens, Eike König and Dorit Merhof
Gaussian Anomaly Detection by Modeling the Distribution of Normal Data in Pre-Trained Deep Features
In: IEEE Transactions on Instrumentation and Measurement

2021

Oliver Rippel and Dorit Merhof
Leveraging pre-trained Segmentation Networks for Anomaly Segmentation
In: IEEE 26th International Conference on Emerging Technologies and Factory Automation (ETFA)

2021

Oliver Rippel, Peter Haumering, Johannes Brauers and Dorit Merhof
Anomaly Detection for the Automated Visual Inspection of PET Preform Closures
In: IEEE 26th International Conference on Emerging Technologies and Factory Automation (ETFA)

2021

Oliver Rippel, Niclas Bilitewski, Khosrow Rahimi, Juliana Kurniadi, Andreas Herrmann and Dorit Merhof
Identifying Pristine and Processed Animal Fibers using Machine Learning
In: IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

2021

Oliver Rippel, Maximilian Müller, Andreas Münkel, Thomas Gries and Dorit Merhof
Estimating the Probability Density Function of new Fabrics for Fabric Anomaly Detection
In: 10th International Conference on Pattern Recognition Applications and Methods (ICPRAM)

2021

Oliver Rippel, Patrick Mertens and Dorit Merhof
Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection
In: 25th International Conference on Pattern Recognition (ICPR)

2020

Dieter Geller, Tarek Stiebel, Oliver Rippel, Volker Lutz, Jonas Osburg, Thomas Gries and Dorit Merhof
Accurate Stitch Position Identification of Sewn Threads in Textiles
In: IEEE 25th International Conference on Emerging Technologies and Factory Automation (ETFA)

2020

Oliver Rippel, Maximilian Müller and Dorit Merhof
GAN-based Defect Synthesis for Anomaly Detection in Fabrics
In: IEEE 25th International Conference on Emerging Technologies and Factory Automation (ETFA)

2020

Johannes Thüring, Oliver Rippel, Christoph Haarburger, Dorit Merhof, Philipp Schad, Philipp Bruners, Christiane K. Kuhl and Daniel Truhn
Multiphase CT-based prediction of Child-Pugh classification: a machine learning approach
In: European Radiology Experimental 4 (1)

2020

Oliver Rippel, Maximilian Schnabel, Georg-Philipp Paar, Thomas Gries and Dorit Merhof
Automated Segmentation of Profiled Fibers in cross-sectional Micrographs for Quality Control
In: IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

2019

Oliver Rippel, Daniel Truhn, Johannes Thüring, Christoph Haarburger, Christiane K. Kuhl and Dorit Merhof
Prediction of Liver Function based on DCE-CT
In: Bildverarbeitung für die Medizin (BVM)

2019

Christoph Haarburger, Justus Schock, Michael Baumgartner, Oliver Rippel and Dorit Merhof
Delira: A High-Level Framework for Deep Learning in Medical Image Analysis
In: Journal of Open Source Software

2019

Christoph Haarburger, Philippe Weitz, Oliver Rippel and Dorit Merhof
Image-based Survival Prediction for Lung Cancer Patients using CNNs
In: IEEE International Symposium on Biomedical Imaging (ISBI)

2018

Leon Weninger, Oliver Rippel, Simon Koppers and Dorit Merhof
Segmentation of Brain Tumors in 3D-MRI Data and Patient Survival Prediction: Methods for the BraTS 2018 Challenge
In: MICCAI Brainlesion Workshop (BrainLes)

Preprints

2018

Rippel, Oliver, Weninger, Leon and Merhof, Dorit
AutoML Segmentation for 3D Medical Image Data: Contribution to the MSD Challenge 2018
In: arXiv preprint arXiv:2005.09978