Dr. Robin Chan

Bergische Universität Wuppertal
Fakultät für Mathematik und Naturwissenschaften
Arbeitsgruppe Stochastik

Lise-Meitner-Str. 27-31
D-42119 Wuppertal

Web: www.robinchan.de

Kontakt:

Raum: FZ.00.02
Tel.: (+49)-(0)202 439 - 1704
E-Mail: chan[at]math.uni-wuppertal.de

Publikationen: Google Scholar

1. Robin Chan, Radin Dardashti, Meike Osinski, Matthias Rottmann, Dominik Brüggemann, Cilia Rücker, Peter Schlicht, Fabian Hüger, Nikol Rummel und Hanno Gottschalk – What Should AI See? Using the Public's Opinion to Determine the Perception of an AI, Preprint, verfügbar: https://arxiv.org/abs/2206.04776
2. Robin Chan, Krzysztof Lis, Svenja Uhlemeyer, Hermann Blum, Sina Honari, Roland Siegwart, Pascal Fua, Mathieu Salzmann und Matthias Rottmann – SegmentMeIfYouCan - A Benchmark for Anomaly Segmentation, 35th Conference on Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track 2021, verfügbar: https://arxiv.org/abs/2104.14812
3. Robin Chan, Matthias Rottmann und Hanno Gottschalk – Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation, The IEEE/CVF International Conference on Computer Vision (ICCV) 2021, verfügbar: https://arxiv.org/abs/2012.06575
4. Dominik Brüggemann, Robin Chan, Hanno Gottschalk und Stefan Bracke – Software Architecture for Human-centered Reliability Assessment for Neural Networks in Autonomous Driving, 11th IMA International Conference on Modelling in Industrial Maintenance and Reliability (MIMAR) 2021, verfügbar: https://uni-w.de/ih7cx
5. Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht und Hanno Gottschalk – MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation, The IEEE International Joint Conference on Neural Networks (IJCNN) 2020, verfügbar: https://arxiv.org/abs/1912.07420
6. Dominik Brüggemann, Robin Chan, Matthias Rottmann, Hanno Gottschalk und Stefan Bracke – Detecting Out Of Distribution Objects in Semantic Segmentation of Street Scenes, The 30th European Safety and Reliability Conference (ESREL) 2020, verfügbar: https://www.rpsonline.com.sg/proceedings/esrel2020/html/4518.xml
7. Matthias Rottmann, Kira Maag, Robin Chan, Fabian Hüger, Peter Schlicht und Hanno Gottschalk – Detection of False Positive and False Negative Samples in Semantic Segmentation, Design, Automation and Test in Europe (DATE) Conference 2020, verfügbar: https://arxiv.org/abs/1912.03673
8. Robin Chan, Matthias Rottmann, Radin Dardashti, Fabian Hüger, Peter Schlicht und Hanno Gottschalk – The Ethical Dilemma when (not) Setting up Cost-based Decision Rules in Semantic Segmentation, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops 2019, verfügbar: https://arxiv.org/abs/1907.01342
9. Robin Chan, Matthias Rottmann, Fabian Hüger, Peter Schlicht und Hanno Gottschalk - Application of Maximum Likelihood Decision Rules for Handling Class Imbalance in Semantic Segmentation, The 30th European Safety and Reliability Conference (ESREL) 2020, verfügbar: https://arxiv.org/abs/1901.08394
10. Matthias Rottmann, Pascal Colling, Thomas-Paul Hack, Robin Chan, Fabian Hüger, Peter Schlicht und Hanno Gottschalk – Prediction Error Meta Classifcation in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities, The IEEE International Joint Conference on Neural Networks (IJCNN) 2020, verfügbar: https://arxiv.org/abs/1811.00648