Hanno Gottschalk
Orcid: 0000-0003-2167-2028
According to our database1,
Hanno Gottschalk
authored at least 64 papers
between 2014 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
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Online presence:
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on zbmath.org
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on orcid.org
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on id.loc.gov
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on d-nb.info
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on dl.acm.org
On csauthors.net:
Bibliography
2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
CoRR, 2024
Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection.
Proceedings of the 19th International Joint Conference on Computer Vision, 2024
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2024, 2024
2023
AI Ethics, November, 2023
J. Optim. Theory Appl., September, 2023
Prediction Quality Meta Regression and Error Meta Classification for Segmented Lidar Point Clouds.
Int. J. Artif. Intell. Tools, August, 2023
VLTSeg: Simple Transfer of CLIP-Based Vision-Language Representations for Domain Generalized Semantic Segmentation.
CoRR, 2023
Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes.
CoRR, 2023
Generalization capabilities of conditional GAN for turbulent flow under changes of geometry.
CoRR, 2023
Equivariant and Steerable Neural Networks: A review with special emphasis on the symmetric group.
CoRR, 2023
Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving.
IEEE Access, 2023
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023
Proceedings of the 18th International Joint Conference on Computer Vision, 2023
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023
Proceedings of the International Joint Conference on Neural Networks, 2023
Who Breaks Early, Looses: Goal Oriented Training of Deep Neural Networks Based on Port Hamiltonian Dynamics.
Proceedings of the Artificial Neural Networks and Machine Learning, 2023
Proceedings of the Artificial Neural Networks and Machine Learning, 2023
Temporal Performance Prediction for Deep Convolutional Long Short-Term Memory Networks.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023
2022
CoRR, 2022
Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning.
CoRR, 2022
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Proceedings of the Computer-Human Interaction Research and Applications, 2022
Proceedings of the 6th International Conference on Computer-Human Interaction Research and Applications, 2022
Proceedings of the Computer Vision - ACCV 2022, 2022
2021
SIAM J. Control. Optim., 2021
SIAM J. Appl. Math., 2021
J. Optim. Theory Appl., 2021
Does Redundancy in AI Perception Systems Help to Test for Super-Human Automated Driving Performance?
CoRR, 2021
CoRR, 2021
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates.
Proceedings of the International Joint Conference on Neural Networks, 2021
False Positive Detection and Prediction Quality Estimation for LiDAR Point Cloud Segmentation.
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.
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.
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.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021
2020
Improving Video Instance Segmentation by Light-weight Temporal Uncertainty Estimates.
CoRR, 2020
CoRR, 2020
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence, 2020
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020
2019
MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation.
CoRR, 2019
Using adjoint CFD to quantify the impact of manufacturing variations on a heavy duty turbine vane.
CoRR, 2019
CoRR, 2019
Comput. Vis. Sci., 2019
The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019
2018
Calibration of léVY Processes using Optimal control of Kolmogorov equations with periodic boundary conditions.
Math. Model. Anal., 2018
Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities.
CoRR, 2018
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2018
2015
J. Optim. Theory Appl., 2015
2014