Maarten Bieshaar

According to our database, Maarten Bieshaar authored at least 37 papers between 2017 and 2024.

Collaborative distances:

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

2024

Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation.

Florian Heidecker, Ahmad El-Khateeb, Maarten Bieshaar, Bernhard Sick

CoRR, 2024

A Safety-Adapted Loss for Pedestrian Detection in Automated Driving.

Maria Lyssenko, Piyush Pimplikar, Maarten Bieshaar, Farzad Nozarian, Rudolph Triebel

CoRR, 2024

A Safety-Adapted Loss for Pedestrian Detection in Autonomous Driving.

Maria Lyssenko, Piyush Pimplikar, Maarten Bieshaar, Farzad Nozarian, Rudolph Triebel

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023

What Does Really Count? Estimating Relevance of Corner Cases for Semantic Segmentation in Automated Driving.

Jasmin Breitenstein, Florian Heidecker, Maria Lyssenko, Daniel Bogdoll, Maarten Bieshaar, J. Marius Zöllner, Bernhard Sick, Tim Fingscheidt

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving.

Kevin Rösch, Florian Heidecker, Julian Truetsch, Kamil Kowol, Clemens Schicktanz, Maarten Bieshaar, Bernhard Sick, Christoph Stiller

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

A Practical Evaluation of Active Learning Approaches for Object Detection.

Jan Schneegans, Maarten Bieshaar, 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

Generating Synthetic Time Series for Machine-Learning-Empowered Monitoring of Electric Motor Test Benches.

Tobias Westmeier, Diego Botache, Maarten Bieshaar, Bernhard Sick

Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

NDNET: A Unified Framework for Anomaly and Novelty Detection.

Jens Decke, Jörn Schmeißing, Diego Botache, Maarten Bieshaar, Bernhard Sick, Christian Gruhl

Proceedings of the Architecture of Computing Systems - 35th International Conference, 2022

2021

Aschaffenburg Pose Dataset.

Viktor Kress, Stefan Zernetsch, Hannes Reichert, Manuel Hetzel, Maarten Bieshaar, Günther Reitberger, Erich Fuchs, Konrad Doll, Bernhard Sick

Dataset, November, 2021

Pedestrians and Cyclists in Road Traffic: Trajectories, 3D Poses and Semantic Maps.

Viktor Kress, Stefan Zernetsch, Maarten Bieshaar, Günther Reitberger, Erich Fuchs, Konrad Doll, Bernhard Sick

Dataset, June, 2021

Cooperative intention detection using machine learning: advanced cyclist protection in the context of automated driving.

Maarten Bieshaar

PhD thesis, 2021

Cyclist Motion State Forecasting - Going beyond Detection.

Maarten Bieshaar, Stefan Zernetsch, Katharina Riepe, Konrad Doll, Bernhard Sick

Proceedings of the IEEE Symposium Series on Computational Intelligence, 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

Probabilistic VRU Trajectory Forecasting for Model-Predictive Planning A Case Study: Overtaking Cyclists.

Jan Schneegans, Jan Eilbrecht, Stefan Zernetsch, Maarten Bieshaar, Konrad Doll, Olaf Stursberg, Bernhard Sick

Proceedings of the IEEE Intelligent Vehicles Symposium Workshops, 2021

An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving.

Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, Bernhard Sick

Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

Description of Corner Cases in Automated Driving: Goals and Challenges.

Daniel Bogdoll, Jasmin Breitenstein, Florian Heidecker, Maarten Bieshaar, Bernhard Sick, Tim Fingscheidt, J. Marius Zöllner

Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021

Out-of-Distribution Detection and Generation Using Soft Brownian Offset Sampling and Autoencoders.

Felix Möller, Diego Botache, Denis Huseljic, Florian Heidecker, Maarten Bieshaar, Bernhard Sick

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Towards Highly Automated Machine-Learning-Empowered Monitoring of Motor Test Stands.

Diego Botache, Florian Bethke, Martin Hardieck, Maarten Bieshaar, Ludwig Brabetz, Mohamed Ayeb, Peter Zipf, Bernhard Sick

Proceedings of the IEEE International Conference on Autonomic Computing and Self-Organizing Systems, 2021

2020

Kooperative Absichtserkennung mittels maschineller Lernverfahren.

Maarten Bieshaar

Proceedings of the Ausgezeichnete Informatikdissertationen 2020., 2020

Quantile Surfaces - Generalizing Quantile Regression to Multivariate Targets.

Maarten Bieshaar, Jens Schreiber, Stephan Vogt, André Gensler, Bernhard Sick

CoRR, 2020

Extended Coopetitive Soft Gating Ensemble.

Stephan Deist, Jens Schreiber, Maarten Bieshaar, Bernhard Sick

CoRR, 2020

Knowledge Representations in Technical Systems - A Taxonomy.

Kristina Scharei, Florian Heidecker, Maarten Bieshaar

CoRR, 2020

Multi-Sensor Data and Knowledge Fusion - A Proposal for a Terminology Definition.

Silvia Beddar-Wiesing, Maarten Bieshaar

CoRR, 2020

Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks.

Jan Schneegans, Maarten Bieshaar, Florian Heidecker, Bernhard Sick

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks.

Florian Heidecker, Abdul Hannan, Maarten Bieshaar, Bernhard Sick

Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

2019

Early Pedestrian Movement Detection Using Smart Devices Based on Human Activity Recognition.

Diego Botache, Dandan Liu, Maarten Bieshaar, Bernhard Sick

Proceedings of the 49. Jahrestagung der Gesellschaft für Informatik, 50 Jahre Gesellschaft für Informatik - Informatik für Gesellschaft, INFORMATIK 2019, 2019

2018

Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble.

Maarten Bieshaar, Stefan Zernetsch, Andreas Hubert, Bernhard Sick, Konrad Doll

IEEE Trans. Intell. Veh., 2018

Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence.

Maarten Bieshaar, Günther Reitberger, Stefan Zernetsch, Bernhard Sick, Erich Fuchs, Konrad Doll

CoRR, 2018

Smart Device based Initial Movement Detection of Cyclists using Convolutional Neuronal Networks.

Jan Schneegans, Maarten Bieshaar

CoRR, 2018

Highly Automated Learning for Improved Active Safety of Vulnerable Road Users.

Maarten Bieshaar, Günther Reitberger, Viktor Kreß, Stefan Zernetsch, Konrad Doll, Erich Fuchs, Bernhard Sick

CoRR, 2018

Where is my Device? - Detecting the Smart Device's Wearing Location in the Context of Active Safety for Vulnerable Road Users.

Maarten Bieshaar

CoRR, 2018

Coopetitive Soft Gating Ensemble.

Jens Schreiber, Maarten Bieshaar, Andre Gensler, Bernhard Sick, Stephan Deist

Proceedings of the 2018 IEEE 3rd International Workshops on Foundations and Applications of Self* Systems (FAS*W), 2018

Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure.

Günther Reitberger, Maarten Bieshaar, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Erich Fuchs

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 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

Starting Movement Detection of Cyclists Using Smart Devices.

Maarten Bieshaar, Malte Depping, Jan Schneegans, Bernhard Sick

Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

2017

Model-predictive planning for autonomous vehicles anticipating intentions of vulnerable road users by artificial neural networks.

Jan Eilbrecht, Maarten Bieshaar, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Olaf Stursberg

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Cooperative starting intention detection of cyclists based on smart devices and infrastructure.

Maarten Bieshaar, Stefan Zernetsch, Malte Depping, Bernhard Sick, Konrad Doll

Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017