Veröffentlichungen

Nachstehend werden wissenschaftliche Beiträge und Veröffentlichungen aus dem Projekt KI Data Tooling aufgeführt.

• Konrad Doll: „KI Data Tooling“: Werkzeugkasten für die künstliche Intelligenz im Automobil. In: Sensorik Magazin, Ausgabe 102, 07/2020.
   
• 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. In: arXiv preprint for SAIAD 2021 Workshop “Safe Artificial Intelligence for Automated Driving”.
   
• Jan Schneegans, Maarten Bieshaar, Florian Heidecker, Bernhard Sick: Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks. In: Pattern Recognition. ICPR International Workshops and Challenges, Virtual Event, 10.-15.01.2021.
   
• Jan Schneegans, Jan Eilbrecht, Stefan Zernetsch, Maarten Bieshaar, Konrad Doll, Olaf Stursberg, Bernhard Sick: Probabilistic VRU Trajectory Forecasting for Model-Predictive PlanningA Case Study: Overtaking Cyclists. In: IEEE IV 2021.
   
• Florian Heidecker, Abdul Hannan, Maarten Bieshaar, Bernhard Sick: Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks. In: ICPR 2021: Pattern Recognition. ICPR International Workshops and Challenges.
   
• Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, and Bernhard Sick: An  Application-Driven  Conceptualization  of  Corner  Casesfor  Perception  in  Highly  Automated  Driving. In: 32nd IEEE Intelligent Vehicles Symposium.
   
• Manuel Hetzel, Hannes Reichert, Konrad Doll, Bernhard Sick: Smart Infrastructure: A research junction. In: 7th IEEE International Smart Cities Conference 2021.
   
• Hannes Reichert, Lukas Lang, Kevin Rösch, Daniel Bogdoll, Konrad Doll, Hans-Christian Reuss, Christoph Stiller, J. Marius Zöllner: Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems. In: 7t IEEE International Smart Cities Conference 2021.
   
• Maarten Bieshaar, Stefan Zernetsch, Katharina Riepe, Konrad Doll, Bernhard Sick: Cyclist Motion State Forecasting – Going beyond Detection. In: 24th IEEE International Conference on Intelligent Transportation Systems - ITSC2021, Indianapolis.
   
• Maarten Bieshaar, Marek Herde, Denis Huselijc, Bernhard Sick: A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving. In: 5th International Workshop on Interactive Adaptive Learning 2021.
   
• Daniel Bogdoll, Jasmin Breitenstein, Florian Heidecker, Maarten Bieshaar, Bernhard Sick, Tim Fingscheidt, J. Marius Zöllner: Description of Corner Cases in Automated Driving: Goals and Challenges. In: ICCV 2021 Workshop on "Embedded and Real-World Computer Vision in Autonomous Driving".
   
• Philipp Rigoll, Patrick Petersen, Jacob Langner, Eric Sax: Parameterizable lidar-assisted traffic sign placement for the augmentation of driving situations with CycleGAN. In: ICSEng 2021: International Conference On Systems Engineering.
   
• Dominik Salles Lukas Lang Martin Kehrer et al.: A Modular Co-Simulation Framework with Open Source Software and Automotive Standards. In: 22. Internationales Stuttgarter Symposium, 15.-16.03.2022.
   
• Philipp Rigoll, Patrick Petersen, Lennart Ries, Jacob Langner und Eric Sax: Augmentation of camera data via Generative Adversarial Networks (GANs) for the validation of automated driving functions. In: 35. VDI Tagung: Fahrerassistenzsysteme und Automatisiertes Fahren, 17.-18.05.2022.
   
• Kamil Kowol, Stefan Bracke, Hanno Gottschalk: A-Eye: Driving with the Eyes of AI for Corner Case Generation. In: 33rd IEEE Intelligent Vehicles Symposium in Aachen, 05.-09.06.2022.
   
• Jonas Löhdefink, Jonas Sitzmann, Andreas Bär, Tim Fingscheidt: Adaptive Bitrate Quantization Scheme Without Codebook for Learned Image Compression. In: CVPR - Workshop, Challenge on Learned Image Compression (CLIC), New Orleans, 19.06.2022.
   
• Jasmin Breitenstein, Tim Fingscheidt: Amodal Cityscapes: A New Dataset, its Generation, and an Amodal Semantic Segmentation Challenge Baseline. In: IV2022, 06.-08.06.2022.
   
• Stefan Zernetsch, Hannes Reichert, Viktor Kreß, Konrad Doll, Bernhard Sick: A Holistic View on Probabilistic Trajectory Forecasting – Case Study: Cyclist Intention Detection. In: IV2022, 06.-08.06.2022.
   
• Daniel Bogdoll, Maximilian Nitsche, J. Marius Zöllner: Anomaly Detection in Autonomous Driving: A Survey. In: CVPR 2022 Workshop on Autonomous Driving, 20.06.2022.