Denis Huseljic

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 29

Top Topics

Active Learning

Top Venues

Trans. Mach. Learn. Res.

Publications

Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification. CoRR (2024)
Marek Herde, Denis Huseljic, Lukas Rauch, Bernhard Sick
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. CoRR (2024)
Marek Herde, Lukas Lührs, Denis Huseljic, Bernhard Sick
Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. CoRR (2024)
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)
Lukas Rauch, Denis Huseljic, Moritz Wirth, Jens Decke, Bernhard Sick, Christoph Scholz
Towards Deep Active Learning in Avian Bioacoustics. CoRR (2024)
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 (2023)
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)
Denis Huseljic, Marek Herde, Paul Hahn, Bernhard Sick
Role of Hyperparameters in Deep Active Learning. IAL@PKDD/ECML (2023)
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)
Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. CoRR (2023)
Marek Herde, Denis Huseljic, Bernhard Sick
Multi-annotator Deep Learning: A Probabilistic Framework for Classification. CoRR (2023)
Marek Herde, Denis Huseljic, Bernhard Sick
Multi-annotator Deep Learning: A Probabilistic Framework for Classification. Trans. Mach. Learn. Res. 2023 (2023)
Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. ECML/PKDD (1) (2023)
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)
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 (2022)
Lukas Rauch, Denis Huseljic, Bernhard Sick
Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources. IAL@PKDD/ECML (2022)
Denis Huseljic, Marek Herde, Mehmet Muejde, Bernhard Sick
A Review of Uncertainty Calibration in Pretrained Object Detectors. CoRR (2022)
Felix Möller, Diego Botache, Denis Huseljic, Florian Heidecker, Maarten Bieshaar, Bernhard Sick
Out-of-Distribution Detection and Generation Using Soft Brownian Offset Sampling and Autoencoders. CVPR Workshops (2021)
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 (2021)
Felix Möller, Diego Botache, Denis Huseljic, Florian Heidecker, Maarten Bieshaar, Bernhard Sick
Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders. CoRR (2021)
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)
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 (2021)
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) (2021)
Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach. CoRR (2020)
Marek Herde, Daniel Kottke, Denis Huseljic, Bernhard Sick
Multi-Annotator Probabilistic Active Learning. ICPR (2020)
Denis Huseljic, Bernhard Sick, Marek Herde, Daniel Kottke
Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks. ICPR (2020)
Daniel Kottke, Jim Schellinger, Denis Huseljic, Bernhard Sick
Limitations of Assessing Active Learning Performance at Runtime. CoRR (2019)
Daniel Kottke, Adrian Calma, Denis Huseljic, Christoph Sandrock, George Kachergis, Bernhard Sick
The Other Human in The Loop - A Pilot Study to Find Selection Strategies for Active Learning. IJCNN (2018)
Daniel Kottke, Adrian Calma, Denis Huseljic, Georg Krempl, Bernhard Sick
Challenges of Reliable, Realistic and Comparable Active Learning Evaluation. IAL@PKDD/ECML (2017)