Marek Herde

According to our database, Marek Herde authored at least 23 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification.

Denis Huseljic, Marek Herde, Yannick Nagel, Lukas Rauch, Paulius Strimaitis, Bernhard Sick

Trans. Mach. Learn. Res., 2024

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans.

Marek Herde, Denis Huseljic, Lukas Rauch, Bernhard Sick

CoRR, 2024

Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification.

Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Tutorial: Interactive Adaptive Learning.

Marek Herde, Tuan Pham Minh, Alaa Tharwat, Bernhard Sick

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), 2024

General Reusability: Ensuring Long-Term Benefits of Deep Active Learning.

Paul Hahn, Denis Huseljic, Marek Herde, Bernhard Sick

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), 2024

Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension.

Marek Herde, Lukas Lührs, Denis Huseljic, Bernhard Sick

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Multi-annotator Deep Learning: A Probabilistic Framework for Classification.

Marek Herde, Denis Huseljic, Bernhard Sick

Trans. Mach. Learn. Res., 2023

Active Label Refinement for Semantic Segmentation of Satellite Images.

Tuan Pham Minh, Jayan Wijesingha, Daniel Kottke, Marek Herde, Denis Huseljic, Bernhard Sick, Michael Wachendorf, Thomas Esch

CoRR, 2023

Role of Hyperparameters in Deep Active Learning.

Denis Huseljic, Marek Herde, Paul Hahn, Bernhard Sick

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 2023), 2023

Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets.

Zhixin Huang, Yujiang He, Marek Herde, Denis Huseljic, Bernhard Sick

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 2023), 2023

Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning.

Marek Herde, Denis Huseljic, Bernhard Sick, Ulrich Bretschneider, Sarah Oeste-Reiß

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 2023), 2023

Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy.

Christoph Sandrock, Marek Herde, Daniel Kottke, Bernhard Sick

Proceedings of the Discovery Science - 26th International Conference, 2023

2022

Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning.

Marek Herde, Zhixin Huang, Denis Huseljic, Daniel Kottke, Stephan Vogt, Bernhard Sick

CoRR, 2022

A Review of Uncertainty Calibration in Pretrained Object Detectors.

Denis Huseljic, Marek Herde, Mehmet Muejde, Bernhard Sick

CoRR, 2022

A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning.

Marek Herde, Denis Huseljic, Jelena Mitrovic, Michael Granitzer, Bernhard Sick

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 2022), 2022

2021

Toward optimal probabilistic active learning using a Bayesian approach.

Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick

Mach. Learn., 2021

A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification.

Marek Herde, Denis Huseljic, Bernhard Sick, Adrian Calma

IEEE Access, 2021

A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving.

Maarten Bieshaar, Marek Herde, Denis Huseljic, Bernhard Sick

Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2021) co-located with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2021), 2021

2020

Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks.

Denis Huseljic, Bernhard Sick, Marek Herde, Daniel Kottke

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Multi-Annotator Probabilistic Active Learning.

Marek Herde, Daniel Kottke, Denis Huseljic, Bernhard Sick

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019

Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields.

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

CoRR, 2019

Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality.

Christoph Sandrock, Marek Herde, Adrian Calma, Daniel Kottke, Bernhard Sick

Proceedings of the International Joint Conference on Neural Networks, 2019

2018

Active Sorting - An Efficient Training of a Sorting Robot with Active Learning Techniques.

Marek Herde, Daniel Kottke, Adrian Calma, Maarten Bieshaar, Stephan Deist, Bernhard Sick

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018