Denis Huseljic

Orcid: 0000-0001-6207-1494

According to our database1, Denis Huseljic authored at least 26 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Legend:

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In proceedings 
Article 
PhD thesis 
Dataset
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Links

On csauthors.net:

Bibliography

2024
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans.
Dataset, June, 2024

The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification.
Trans. Mach. Learn. Res., 2024

Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Towards Deep Active Learning in Avian Bioacoustics.
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.
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.
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.
Trans. Mach. Learn. Res., 2023

Active Label Refinement for Semantic Segmentation of Satellite Images.
CoRR, 2023

ActiveGLAE: A Benchmark for Deep Active Learning with Transformers.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Role of Hyperparameters in Deep Active Learning.
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.
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.
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

2022
Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning.
CoRR, 2022

A Review of Uncertainty Calibration in Pretrained Object Detectors.
CoRR, 2022

Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources.
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

A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning.
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.
Mach. Learn., 2021

A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification.
IEEE Access, 2021

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

Out-of-Distribution Detection and Generation Using Soft Brownian Offset Sampling and Autoencoders.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Multi-Annotator Probabilistic Active Learning.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
Limitations of Assessing Active Learning Performance at Runtime.
CoRR, 2019

2018
The Other Human in The Loop - A Pilot Study to Find Selection Strategies for Active Learning.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017
Challenges of Reliable, Realistic and Comparable Active Learning Evaluation.
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), 2017


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