Matthias Rottmann

Comput. Phys. Commun., November, 2023

What should AI see? Using the public's opinion to determine the perception of an AI.

[BibT_eX]

[DOI]

AI Ethics, November, 2023

Detection of Iterative Adversarial Attacks via Counter Attack.

[BibT_eX]

[DOI]

J. Optim. Theory Appl., September, 2023

Prediction Quality Meta Regression and Error Meta Classification for Segmented Lidar Point Clouds.

[BibT_eX]

[DOI]

Int. J. Artif. Intell. Tools, August, 2023

Uncertainty quantification for deep learning-based schemes for solving high-dimensional backward stochastic differential equations.

[BibT_eX]

[DOI]

Lorenc Kapllani

Long Teng

CoRR, 2023

ResBuilder: Automated Learning of Depth with Residual Structures.

[BibT_eX]

[DOI]

CoRR, 2023

Automated Detection of Label Errors in Semantic Segmentation Datasets via Deep Learning and Uncertainty Quantification.

[BibT_eX]

[DOI]

Marco Reese

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Semi-Supervised Domain Adaptation with CycleGAN Guided by Downstream Task Awareness.

[BibT_eX]

[DOI]

Annika Mütze

Proceedings of the 18th International Joint Conference on Computer Vision, 2023

False Negative Reduction in Semantic Segmentation Under Domain Shift Using Depth Estimation.

[BibT_eX]

[DOI]

Kira Maag

Proceedings of the 18th International Joint Conference on Computer Vision, 2023

MGiaD: Multigrid in all dimensions. Efficiency and robustness by weight sharing and coarsening in resolution and channel dimensions.

[BibT_eX]

[DOI]

Antonia van Betteray

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

LMD: Light-Weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 45th DAGM German Conference, 2023

2022

AttEntropy: Segmenting Unknown Objects in Complex Scenes using the Spatial Attention Entropy of Semantic Segmentation Transformers.

[BibT_eX]

[DOI]

CoRR, 2022

MGiaD: Multigrid in all dimensions. Efficiency and robustness by coarsening in resolution and channel dimensions.

[BibT_eX]

[DOI]

Antonia van Betteray

CoRR, 2022

Semi-supervised domain adaptation with CycleGAN guided by a downstream task loss.

[BibT_eX]

[DOI]

Annika Mütze

CoRR, 2022

Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Detecting and Learning the Unknown in Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, 2022

Towards unsupervised open world semantic segmentation.

[BibT_eX]

[DOI]

Svenja Uhlemeyer

Proceedings of the Uncertainty in Artificial Intelligence, 2022

UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs.

[BibT_eX]

[DOI]

Philipp Oberdiek

Gernot A. Fink

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

HD Lane Map Generation Based on Trail Map Aggregation.

[BibT_eX]

[DOI]

Pascal Colling

Dennis Müller

Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

2021

A multigrid accelerated eigensolver for the Hermitian Wilson-Dirac operator in lattice QCD.

[BibT_eX]

[DOI]

Comput. Phys. Commun., 2021

Does Redundancy in AI Perception Systems Help to Test for Super-Human Automated Driving Performance?

[BibT_eX]

[DOI]

Maida Saltagic

CoRR, 2021

Background-Foreground Segmentation for Interior Sensing in Automotive Industry.

[BibT_eX]

[DOI]

CoRR, 2021

Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety.

[BibT_eX]

[DOI]

CoRR, 2021

SegmentMeIfYouCan: A Benchmark for Anomaly Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis.

[BibT_eX]

[DOI]

Proceedings of the IEEE Intelligent Vehicles Symposium Workshops, 2021

MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection.

[BibT_eX]

[DOI]

Marius Schubert

Proceedings of the International Joint Conference on Neural Networks, 2021

Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates.

[BibT_eX]

[DOI]

Proceedings of the International Joint Conference on Neural Networks, 2021

False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentation.

[BibT_eX]

[DOI]

Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

MetaBox+: A New Region based Active Learning Method for Semantic Segmentation using Priority Maps.

[BibT_eX]

[DOI]

Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, 2021

Entropy Maximization and Meta Classification for Out-of-Distribution Detection in Semantic Segmentation.

[BibT_eX]

[DOI]

Robin Chan

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

YOdar: Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors.

[BibT_eX]

[DOI]

Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

2020

Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates.

[BibT_eX]

[DOI]

CoRR, 2020

A Convenient Infinite Dimensional Framework for Generative Adversarial Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Detection of Iterative Adversarial Attacks via Counter Attack.

[BibT_eX]

[DOI]

CoRR, 2020

Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Controlled False Negative Reduction of Minority Classes in Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks.

[BibT_eX]

[DOI]

Kira Maag

Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020

Detection of False Positive and False Negative Samples in Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

Detection and Retrieval of Out-of-Distribution Objects in Semantic Segmentation.

[BibT_eX]

[DOI]

Philipp Oberdiek

Gernot A. Fink

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, 2019

Application of Decision Rules for Handling Class Imbalance in Semantic Segmentation.

[BibT_eX]

[DOI]

CoRR, 2019

Period Index: A Learned 2D Hash Index for Range and Duration Queries.

[BibT_eX]

[DOI]

Proceedings of the 16th International Symposium on Spatial and Temporal Databases, 2019

Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images.

[BibT_eX]

[DOI]

Marius Schubert

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

2018

Least Angle Regression Coarsening in Bootstrap Algebraic Multigrid.

[BibT_eX]

[DOI]

SIAM J. Sci. Comput., 2018

Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities.

[BibT_eX]

[DOI]

CoRR, 2018

Deep Bayesian Active Semi-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Classification Uncertainty of Deep Neural Networks Based on Gradient Information.

[BibT_eX]

[DOI]

Philipp Oberdiek