| Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks D Huseljic, B Sick, M Herde, D Kottke International Conference on Pattern Recognition, 9172-9179, 2021 | 24 | 2021 |
| Toward optimal probabilistic active learning using a Bayesian approach D Kottke, M Herde, C Sandrock, D Huseljic, G Krempl, B Sick Machine Learning 110 (6), 1199-1231, 2021 | 23 | 2021 |
| A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification M Herde, D Huseljic, B Sick, A Calma IEEE Access, 2021 | 21 | 2021 |
| Active Sorting – An Efficient Training of a Sorting Robot with Active Learning Techniques M Herde, D Kottke, A Calma, M Bieshaar, S Deist, B Sick International Joint Conference on Neural Networks, 1-8, 2018 | 9 | 2018 |
| Collaborative Interactive Learning – A clarification of terms and a differentiation from other research fields T Hanika, M Herde, J Kuhn, JM Leimeister, P Lukowicz, S Oeste-Reiß, ... arXiv preprint arXiv:1905.07264, 2019 | 8 | 2019 |
| scikit-activeml: A library and toolbox for active learning algorithms D Kottke, M Herde, TP Minh, A Benz, P Mergard, A Roghman, C Sandrock, ... Preprints, 2021 | 7 | 2021 |
| Multi-annotator Probabilistic Active Learning M Herde, D Kottke, D Huseljic, B Sick International Conference on Pattern Recognition, 10281-10288, 2021 | 6 | 2021 |
| Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality C Sandrock, M Herde, A Calma, D Kottke, B Sick International Joint Conference on Neural Networks, 1-8, 2019 | 5 | 2019 |
| Automated Active Learning with a Robot K Scharei, M Herde, M Bieshaar, A Calma, D Kottke, B Sick Archives of Data Science, Series A 5 (1), 16, 2018 | 3 | 2018 |
| Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning M Herde, D Huseljic, B Sick, U Bretschneider, S Oeste-Reiß International Workshop on Interactive Adaptive Learning @ European …, 2023 | 1 | 2023 |
| Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning M Herde, Z Huang, D Huseljic, D Kottke, S Vogt, B Sick arXiv preprint arXiv:2210.06112, 2022 | 1 | 2022 |
| Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification D Huseljic, P Hahn, M Herde, L Rauch, B Sick arXiv preprint arXiv:2404.08981, 2024 | | 2024 |
| Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy C Sandrock, M Herde, D Kottke, B Sick International Conference on Discovery Science, 265-276, 2023 | | 2023 |
| Role of Hyperparameters in Deep Active Learning D Huseljic, M Herde, P Hahn, B Sick International Workshop on Interactive Adaptive Learning @ European …, 2023 | | 2023 |
| Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets Z Huang, Y He, M Herde, D Huseljic, B Sick International Workshop on Interactive Adaptive Learning @ European …, 2023 | | 2023 |
| Active Label Refinement for Semantic Segmentation of Satellite Images TP Minh, J Wijesingha, D Kottke, M Herde, D Huseljic, B Sick, ... arXiv preprint arXiv:2309.06159, 2023 | | 2023 |
| Multi-annotator Deep Learning: A Probabilistic Framework for Classification M Herde, D Huseljic, B Sick Transactions on Machine Learning Research, 2023 | | 2023 |
| A Review of Uncertainty Calibration in Pretrained Object Detectors D Huseljic, M Herde, M Muejde, B Sick arXiv preprint arXiv:2210.02935, 2022 | | 2022 |
| A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving M Bieshaar, M Herde, D Huseljic, B Sick International Workshop on Interactive Adaptive Learning @ European …, 2021 | | 2021 |
Bernhard SickProfessor of Intelligent Embedded Systems, University of KasselBestätigte E-Mail-Adresse bei uni-kassel.de
