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2020 – today
- 2025
[j5]Denis Huseljic
, Marek Herde, Paul Hahn, Mehmet Muejde, Bernhard Sick:
Systematic Evaluation of Uncertainty Calibration in Pretrained Object Detectors. Int. J. Comput. Vis. 133(3): 1033-1047 (2025)- 2024
- [j4]Denis Huseljic, Marek Herde, Yannick Nagel, Lukas Rauch, Paulius Strimaitis, Bernhard Sick:
The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification. Trans. Mach. Learn. Res. 2024 (2024) - [c15]Marek Herde, Lukas Lührs, Denis Huseljic, Bernhard Sick:
Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. ECAI 2024: 2910-2918 - [c14]Marek Herde, Tuan Pham Minh, Alaa Tharwat, Bernhard Sick:
Tutorial: Interactive Adaptive Learning. IAL@PKDD/ECML 2024: 1-6 - [c13]Paul Hahn, Denis Huseljic, Marek Herde, Bernhard Sick:
General Reusability: Ensuring Long-Term Benefits of Deep Active Learning. IAL@PKDD/ECML 2024: 33-46 - [c12]Marek Herde, Denis Huseljic, Lukas Rauch, Bernhard Sick:
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. NeurIPS 2024 - [c11]Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick:
Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification. ECML/PKDD (7) 2024: 280-296 - [e1]Mirko Bunse, Marek Herde, Georg Krempl, Vincent Lemaire, Alaa Tharwat, Minh Tuan Pham, Amal Saadallah:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, September 9th, 2024. CEUR Workshop Proceedings 3770, CEUR-WS.org 2024 [contents] - [d1]Marek Herde, Denis Huseljic, Lukas Rauch, Bernhard Sick:
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. Zenodo, 2024
- [i10]Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick:
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification. CoRR abs/2404.08981 (2024) - [i9]Marek Herde, Lukas Lührs, Denis Huseljic, Bernhard Sick:
Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. CoRR abs/2405.03386 (2024) - [i8]Marek Herde, Denis Huseljic, Lukas Rauch, Bernhard Sick:
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. CoRR abs/2407.20950 (2024) - 2023
- [j3]Marek Herde, Denis Huseljic, Bernhard Sick:
Multi-annotator Deep Learning: A Probabilistic Framework for Classification. Trans. Mach. Learn. Res. 2023 (2023) - [c10]Christoph Sandrock, Marek Herde, Daniel Kottke, Bernhard Sick:
Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy. DS 2023: 265-276 - [c9]Marek Herde, Denis Huseljic, Bernhard Sick, Ulrich Bretschneider, Sarah Oeste-Reiß:
Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning. IAL@PKDD/ECML 2023: 14-18 - [c8]Denis Huseljic, Marek Herde, Paul Hahn, Bernhard Sick:
Role of Hyperparameters in Deep Active Learning. IAL@PKDD/ECML 2023: 19-24 - [c7]Zhixin Huang, Yujiang He, Marek Herde, Denis Huseljic, Bernhard Sick:
Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets. IAL@PKDD/ECML 2023: 25-45 - [i7]Marek Herde, Denis Huseljic, Bernhard Sick:
Multi-annotator Deep Learning: A Probabilistic Framework for Classification. CoRR abs/2304.02539 (2023) - [i6]Tuan Pham Minh, Jayan Wijesingha, Daniel Kottke, Marek Herde, Denis Huseljic, Bernhard Sick, Michael Wachendorf, Thomas Esch:
Active Label Refinement for Semantic Segmentation of Satellite Images. CoRR abs/2309.06159 (2023) - 2022
- [c6]Marek Herde, Denis Huseljic, Jelena Mitrovic, Michael Granitzer, Bernhard Sick:
A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning. IAL@PKDD/ECML 2022: 1-6 - [i5]Denis Huseljic, Marek Herde, Mehmet Muejde, Bernhard Sick:
A Review of Uncertainty Calibration in Pretrained Object Detectors. CoRR abs/2210.02935 (2022) - [i4]Marek Herde, Zhixin Huang, Denis Huseljic, Daniel Kottke, Stephan Vogt, Bernhard Sick:
Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning. CoRR abs/2210.06112 (2022) - 2021
- [j2]Marek Herde, Denis Huseljic, Bernhard Sick, Adrian Calma:
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification. IEEE Access 9: 166970-166989 (2021) - [j1]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward optimal probabilistic active learning using a Bayesian approach. Mach. Learn. 110(6): 1199-1231 (2021) - [c5]Maarten Bieshaar, Marek Herde, Denis Huseljic, Bernhard Sick:
A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving. IAL@PKDD/ECML 2021: 65-69 - [i3]Marek Herde, Denis Huseljic, Bernhard Sick, Adrian Calma:
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification. CoRR abs/2109.11301 (2021) - 2020
- [c4]Denis Huseljic, Bernhard Sick, Marek Herde, Daniel Kottke:
Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks. ICPR 2020: 9172-9179 - [c3]Marek Herde, Daniel Kottke, Denis Huseljic, Bernhard Sick:
Multi-Annotator Probabilistic Active Learning. ICPR 2020: 10281-10288 - [i2]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach. CoRR abs/2006.01732 (2020)
2010 – 2019
- 2019
- [c2]Christoph Sandrock, Marek Herde, Adrian Calma, Daniel Kottke, Bernhard Sick:
Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality. IJCNN 2019: 1-8 - [i1]Tom Hanika, Marek Herde, Jochen Kuhn, Jan Marco Leimeister, Paul Lukowicz, Sarah Oeste-Reiß, Albrecht Schmidt, Bernhard Sick, Gerd Stumme, Sven Tomforde, Katharina Anna Zweig:
Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields. CoRR abs/1905.07264 (2019) - 2018
- [c1]Marek Herde, Daniel Kottke, Adrian Calma, Maarten Bieshaar, Stephan Deist, Bernhard Sick:
Active Sorting - An Efficient Training of a Sorting Robot with Active Learning Techniques. IJCNN 2018: 1-8
Coauthor Index
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last updated on 2025-04-03 00:22 CEST by the dblp team
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