| Learning convolutional neural networks for object detection with very little training data C Reinders, H Ackermann, MY Yang, B Rosenhahn Multimodal scene understanding, 65-100, 2019 | 43 | 2019 |
| Region-based cycle-consistent data augmentation for object detection F Kluger, C Reinders, K Raetz, P Schelske, B Wandt, H Ackermann, ... 2018 IEEE International Conference on Big Data (Big Data), 5205-5211, 2018 | 27 | 2018 |
| Roadsaw: A large-scale dataset for camera-based road surface and wetness estimation K Cordes, C Reinders, P Hindricks, J Lammers, B Rosenhahn, H Broszio Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 18 | 2022 |
| Object recognition from very few training examples for enhancing bicycle maps C Reinders, H Ackermann, MY Yang, B Rosenhahn 2018 IEEE Intelligent Vehicles Symposium (IV), 1-8, 2018 | 17 | 2018 |
| Constrained mean shift clustering M Schier, C Reinders, B Rosenhahn Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 12 | 2022 |
| Deep reinforcement learning for autonomous driving using high-level heterogeneous graph representations M Schier, C Reinders, B Rosenhahn 2023 IEEE International Conference on Robotics and Automation (ICRA), 7147-7153, 2023 | 9 | 2023 |
| Blind knowledge distillation for robust image classification T Kaiser, L Ehmann, C Reinders, B Rosenhahn arXiv preprint arXiv:2211.11355, 2022 | 9 | 2022 |
| ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing C Reinders, F Schubert, B Rosenhahn 31st International Joint Conference on Artificial Intelligence and the 25th …, 2022 | 8 | 2022 |
| Compensation learning in semantic segmentation T Kaiser, C Reinders, B Rosenhahn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 3 | 2023 |
| Two Worlds in One Network: Fusing Deep Learning and Random Forests for Classification and Object Detection C Reinders, MY Yang, B Rosenhahn Volunteered Geographic Information, 103, 2024 | 2 | 2024 |
| Learned Fourier Bases for Deep Set Feature Extractors in Automotive Reinforcement Learning M Schier, C Reinders, B Rosenhahn 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 2 | 2023 |
| Learning a Fully Convolutional Network for Object Recognition using very few Data C Reinders, H Ackermann, MY Yang, B Rosenhahn arXiv preprint arXiv:1709.05910, 2017 | 2 | 2017 |
| Neural Random Forest Imitation C Reinders, B Rosenhahn arXiv preprint arXiv:1911.10829, 2019 | 1 | 2019 |
| On-the-fly handwriting recognition using a high-level representation C Reinders, F Baumann, B Scheuermann, A Ehlers, N Mühlpforte, ... Computer Analysis of Images and Patterns: 16th International Conference …, 2015 | 1 | 2015 |
| RAW-Diffusion: RGB-Guided Diffusion Models for High-Fidelity RAW Image Generation C Reinders, R Berdan, B Besbinar, J Otsuka, D Iso arXiv preprint arXiv:2411.13150, 2024 | | 2024 |
| Supplementary Material: Compensation Learning in Semantic Segmentation T Kaiser, C Reinders, B Rosenhahn | | |
