| Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks D Huseljic, B Sick, M Herde, D Kottke ICPR, 2021 | 30 | 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 | 29 | 2021 |
| Toward optimal probabilistic active learning using a Bayesian approach D Kottke, M Herde, C Sandrock, D Huseljic, G Krempl, B Sick MLJ, 2021 | 28 | 2021 |
| scikit-activeml: A library and toolbox for active learning algorithms D Kottke, M Herde, A Benz, P Mergard, A Roghman, C Sandrock, B Sick | 11 | 2021 |
| 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 | 9 | 2019 |
| 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 IJCNN, 2018 | 9 | 2018 |
| Multi-annotator Probabilistic Active Learning M Herde, D Kottke, D Huseljic, B Sick ICPR, 2021 | 8 | 2021 |
| Multi-annotator Deep Learning: A Probabilistic Framework for Classification M Herde, D Huseljic, B Sick TMLR, 2023 | 7 | 2023 |
| Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality C Sandrock, M Herde, A Calma, D Kottke, B Sick IJCNN, 2019 | 5 | 2019 |
| Role of Hyperparameters in Deep Active Learning D Huseljic, M Herde, P Hahn, B Sick ECML-PKDD: IAL Workshop, 2023 | 3 | 2023 |
| 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 |
| Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension M Herde, L Lührs, D Huseljic, B Sick ECAI, 2024 | 2 | 2024 |
| BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics L Rauch, R Schwinger, M Wirth, R Heinrich, D Huseljic, M Herde, J Lange, ... arXiv preprint arXiv:2403.10380, 2024 | 2 | 2024 |
| Efficient Bayesian Updates for Deep Active Learning via Laplace Approximations D Huseljic, M Herde, L Rauch, P Hahn, Z Huang, S Vogt, D Kottke, B Sick arXiv preprint arXiv:2210.06112, 2024 | 2* | 2024 |
| Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification D Huseljic, P Hahn, M Herde, L Rauch, B Sick ECML-PKDD, 2024 | 1 | 2024 |
| The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification D Huseljic, M Herde, Y Nagel, L Rauch, P Strimaitis, B Sick TMLR, 2024 | 1 | 2024 |
| Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning M Herde, D Huseljic, B Sick, U Bretschneider, S Oeste-Reiß IAL Workshop @ ECML-PKDD, 14-18, 2023 | 1 | 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 | 1 | 2023 |
| Systematic Evaluation of Uncertainty Calibration in Pretrained Object Detectors D Huseljic, M Herde, P Hahn, M Müjde, B Sick IJCV, 2024 | | 2024 |
| dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans M Herde, D Huseljic, L Rauch, B Sick NeurIPS: D&B Track, 2024 | | 2024 |
Bernhard SickProfessor of Intelligent Embedded Systems, University of KasselEmail được xác minh tại uni-kassel.de
