Showing results 121 - 140 out of 719
2020
Busch, A., Fink, D., Laves, M. H., Ziaukas, Z., Wielitzka, M., & Ortmaier, T. (2020). Classification of Road Surface and Weather-Related Condition Using Deep Convolutional Neural Networks. In M. Klomp, F. Bruzelius, J. Nielsen, & A. Hillemyr (Eds.), Advances in Dynamics of Vehicles on Roads and Tracks: Proceedings of the 26th Symposium of the International Association of Vehicle System Dynamics, IAVSD 2019, August 12-16, 2019, Gothenburg, Sweden (pp. 1042-1051). (Lecture Notes in Mechanical Engineering). Springer Nature. https://doi.org/10.1007/978-3-030-38077-9_121
Ehlers, S. F. G., Stuede, M., Nülle, K., & Ortmaier, T. (2020). Map Management Approach for SLAM in Large-Scale Indoor and Outdoor Areas. In 2020 IEEE International Conference on Robotics and Automation, ICRA 2020 (pp. 9652-9658). Article 9196997 https://doi.org/10.15488/10360, https://doi.org/10.1109/icra40945.2020.9196997
Fast, J. F., Westermann, K. A., Laves, M.-H. V., Jungheim, M., Ptok, M., Ortmaier, T., & Kahrs, L. A. (2020). Droplet applicator module for reproducible and controlled endoscopic laryngeal adductor reflex stimulation. BIOMICROFLUIDICS, 14(4), Article 044112. https://doi.org/10.1063/5.0004351
Ferle, M. (2020). The soft-tissue restraints of the knee and its balancing capacity in total knee arthroplasty procedures. [Doctoral thesis, Leibniz University Hannover]. Leibniz Universität Hannover. https://doi.org/10.15488/9976
Fink, D., Busch, A., Wielitzka, M., & Ortmaier, T. (2020). Resource Efficient Classification of Road Conditions through CNN Pruning. In 21st IFAC World Congress (2 ed., Vol. 53, pp. 13958-13963). (IFAC-PapersOnLine).. https://doi.org/10.1016/j.ifacol.2020.12.913
Frank, T., Wieting, S., Wielitzka, M., Bosselmann, S., & Ortmaier, T. (2020). Identification of temperature-dependent boundary conditions using MOR. International Journal of Numerical Methods for Heat and Fluid Flow, 30(2), 1009-1022. https://doi.org/10.1108/hff-05-2019-0404
Frank, T., Zeipel, H., Wielitzka, M., Bosselmann, S., & Ortmaier, T. (2020). Real-Time Prediction of Curing Processes using Model Order Reduction. IFAC-PapersOnLine, 53(2), 11132-11137. https://doi.org/10.1016/j.ifacol.2020.12.273
Frank, T., Wielitzka, M., & Ortmaier, T. (2020). Reduced-Order Kalman Filter for Surface Temperature Monitoring of parameter-variant thermal Systems. In 2020 IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 570-575). (IEEE International Conference on Mechatronics and Automation). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMA49215.2020.9233772
Frank, T., Wielitzka, M., Dagen, M., & Ortmaier, T. (2020). Reduced-Order Modeling of Parameter Variations for Parameter Identification in Rubber Curing. In O. Gusikhin, K. Madani, & J. Zaytoon (Eds.), ICINCO 2020 - Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics (pp. 659-666)
Hansen, C. (2020). Planung energieeffizienter Mehrachstrajektorien unter Ausnutzung elektrischer Antriebskopplung. [Doctoral thesis, Leibniz University Hannover]. TEWISS Verlag.
Ihler, S., Laves, M.-H., & Ortmaier, T. (2020). Patient-Specific Domain Adaptation for Fast Optical Flow Based on Teacher-Student Knowledge Transfer. Advance online publication. https://arxiv.org/abs/2007.04928
Ihler, S., Kuhnke, F. K., Laves, M.-H. V., & Ortmaier, T. (2020). Self-Supervised Domain Adaptation for Patient-Specific, Real-Time Tissue Tracking. In A. L. Martel, P. Abolmaesumi, D. Stoyanov, D. Mateus, M. A. Zuluaga, S. K. Zhou, D. Racoceanu, & L. Joskowicz (Eds.), International Conference on Medical Image Computing and Computer Assisted Intervention (pp. 54-64). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12263 LNCS). Springer, Cham. https://doi.org/10.1007/978-3-030-59716-0_6
Jahn, T., Ziaukas, Z., Kobler, J. P., Wielitzka, M., & Ortmaier, T. (2020). Neural Observer for Nonlinear State and Input Estimation in a Truck-Semitrailer Combination. IFAC-PapersOnLine, 53(2), 14306-14311. https://doi.org/10.1016/j.ifacol.2020.12.1372
Kaczor, D., Bensch, M., Schappler, M., & Ortmaier, T. (2020). Trajectory optimization for the handling of elastically coupled objects via reinforcement learning and flatness-based control. In Annals of scientific society for assembly, handling and industrial robotics (pp. 319-329). Springer Verlag. https://doi.org/10.1007/978-3-662-61755-7_29
Knöchelmann, E., Steinke, D., Greenyer, J., Spindeldreier, S., & Ortmaier, T. (2020). Trajectory Optimization Methods for Robotic Cells Considering Energy Efficiency and Collisions. In T. Schüppstuhl, K. Tracht, & D. Henrich (Eds.), Annals of Scientific Society for Assembly, Handling and Industrial Robotics (pp. 229–240). Springer Vieweg. https://doi.org/10.1007/978-3-662-61755-7_21, https://doi.org/10.15488/10378
Kortmann, K. P., Zumsande, J., Wielitzka, M., & Ortmaier, T. (2020). Temporal Object Tracking in Large-Scale Production Facilities using Bayesian Estimation. IFAC-PapersOnLine, 53(2), 11125-11131. https://doi.org/10.1016/j.ifacol.2020.12.271
Laves, M.-H., Ihler, S., Kortmann, K.-P., & Ortmaier, T. (2020). Calibration of Model Uncertainty for Dropout Variational Inference. Advance online publication. https://arxiv.org/abs/2006.11584
Laves, M.-H., Tölle, M., & Ortmaier, T. (2020). Uncertainty Estimation in Medical Image Denoising with Bayesian Deep Image Prior. In C. H. Sudre, H. Fehri, T. Arbel, C. F. Baumgartner, A. Dalca, R. Tanno, K. Van Leemput, W. M. Wells, A. Sotiras, B. Papiez, E. Ferrante, & S. Parisot (Eds.), Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis (pp. 81-96). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12443 LNCS). Springer, Cham. https://doi.org/10.1007/978-3-030-60365-6_9
Laves, M. H., Ihler, S., Fast, J. F., Kahrs, L. A., & Ortmaier, T. (2020). Well-Calibrated Regression Uncertainty in Medical Imaging with Deep Learning. Proceedings of Machine Learning Research, 121, 393-412. https://proceedings.mlr.press/v121/laves20a.html
Männel, A., Müller, K., Knöchelmann, E., & Ortmaier, T. (2020). Load Profile Cycle Recognition for Industrial DC Microgrids with Energy Storage Systems. In 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE) (pp. 904-911). (Proceedings of the IEEE International Symposium on Industrial Electronics; Vol. 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.15488/10381, https://doi.org/10.1109/ISIE45063.2020.9152432