Cooperative starting intention detection of cyclists based on smart devices and infrastructure. - Maarten Bieshaar; Stefan Zernetsch; Malte Depping; Bernhard Sick; Konrad Doll (ITSC, 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 (SSCI, 2017)

Starting Movement Detection of Cyclists Using Smart Devices. - Maarten Bieshaar; Malte Depping; Jan Schneegans; Bernhard Sick (DSAA, 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 (IJCNN, 2018)

Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure. - Günther Reitberger; Maarten Bieshaar; Stefan Zernetsch; Konrad Doll; Bernhard Sick; Erich Fuchs (ITSC, 2018)

Coopetitive Soft Gating Ensemble. - Jens Schreiber; Maarten Bieshaar; Andre Gensler; Bernhard Sick; Stephan Deist (FAS*W@SASO/ICAC, 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)

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)

Smart Device based Initial Movement Detection of Cyclists using Convolutional Neuronal Networks. - Jan Schneegans; Maarten Bieshaar (CoRR, 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)

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)

Early Pedestrian Movement Detection Using Smart Devices Based on Human Activity Recognition. - Diego Botache; Dandan Liu; Maarten Bieshaar; Bernhard Sick (GI-Jahrestagung (Workshops), 2019)

Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks. - Florian Heidecker; Abdul Hannan; Maarten Bieshaar; Bernhard Sick (ICPR Workshops (4), 2020)

Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks. - Jan Schneegans; Maarten Bieshaar; Florian Heidecker; Bernhard Sick (ICPR Workshops (4), 2020)

Multi-Sensor Data and Knowledge Fusion - A Proposal for a Terminology Definition. - Silvia Beddar-Wiesing; Maarten Bieshaar (CoRR, 2020)

Knowledge Representations in Technical Systems - A Taxonomy. - Kristina Scharei; Florian Heidecker; Maarten Bieshaar (CoRR, 2020)

Extended Coopetitive Soft Gating Ensemble. - Stephan Deist; Jens Schreiber; Maarten Bieshaar; Bernhard Sick (CoRR, 2020)

Quantile Surfaces - Generalizing Quantile Regression to Multivariate Targets. - Maarten Bieshaar; Jens Schreiber; Stephan Vogt; André Gensler; Bernhard Sick (CoRR, 2020)

Kooperative Absichtserkennung mittels maschineller Lernverfahren. - Maarten Bieshaar (Ausgezeichnete Informatikdissertationen, 2020)

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 (ACSOS, 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 (CVPR Workshops, 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 (ICCVW, 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 (IV, 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 (IV Workshops, 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 (IAL@PKDD/ECML, 2021)

Cyclist Motion State Forecasting - Going beyond Detection. - Maarten Bieshaar; Stefan Zernetsch; Katharina Riepe; Konrad Doll; Bernhard Sick (SSCI, 2021)

Cooperative intention detection using machine learning: advanced cyclist protection in the context of automated driving. - Maarten Bieshaar (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 (Zenodo, 2021)

Aschaffenburg Pose Dataset. - Viktor Kress; Stefan Zernetsch; Hannes Reichert; Manuel Hetzel; Maarten Bieshaar; Günther Reitberger; Erich Fuchs; Konrad Doll; Bernhard Sick (Zenodo, 2021)

NDNET: A Unified Framework for Anomaly and Novelty Detection. - Jens Decke; Jörn Schmeißing; Diego Botache; Maarten Bieshaar; Bernhard Sick; Christian Gruhl (ARCS, 2022)

Generating Synthetic Time Series for Machine-Learning-Empowered Monitoring of Electric Motor Test Benches. - Tobias Westmeier; Diego Botache; Maarten Bieshaar; Bernhard Sick (DSAA, 2022)

A Practical Evaluation of Active Learning Approaches for Object Detection. - Jan Schneegans; Maarten Bieshaar; Bernhard Sick (IAL@PKDD/ECML, 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 (SSCI, 2022)

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 (ICCV (Workshops), 2023)

A Safety-Adapted Loss for Pedestrian Detection in Autonomous Driving. - Maria Lyssenko; Piyush Pimplikar; Maarten Bieshaar; Farzad Nozarian; Rudolph Triebel (ICRA, 2024)

A Safety-Adapted Loss for Pedestrian Detection in Automated Driving. - Maria Lyssenko; Piyush Pimplikar; Maarten Bieshaar; Farzad Nozarian; Rudolph Triebel (CoRR, 2024)

Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation. - Florian Heidecker; Ahmad El-Khateeb; Maarten Bieshaar; Bernhard Sick (CoRR, 2024)

A Concept for Requirements-Driven Identification and Mitigation of Dataset Gaps for Perception Tasks in Automated Driving. - Mohamed Sabry Moustafa; Maarten Bieshaar; Andreas Albrecht; Bernhard Sick (ICPRAM, 2025)