Biblio
3D-Extended Object Tracking and Shape Classification with a Lidar Sensor using Random Matrices and Virtual Measurement Models.
27th International Conference on Information Fusion (FUSION). 1-8.
(2024). Enhancing Inland Water Safety: The Lake Constance Obstacle Detection Benchmark.
IEEE International Conference on Robotics and Automation (ICRA). 14808-14814.
(2024). Bayesian Calibration of MEMS Accelerometers.
IEEE Sensors Journal.
(2023). Deep probabilistic modelling for energy forecasting.
Poster_Deep probabilistic modelling for energy forecasting TTT.pdf (839.27 KB)
(2023). Deep transformation models for functional outcome prediction after acute ischemic stroke.
Biometrical Journal. 65, 2100379.
(2023).
(2023). Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model.
International Conference on Information Fusion (FUSION). 1-8.
(2023). Incremental one-class learning using regularized null-space training for industrial defect detection.
16th International Conference on Machine Vision (ICMV).
(2023). Novel AI-Based Algorithm for the Automated Computation of Coronal Parameters in Adolescent Idiopathic Scoliosis Patients: A Validation Study on 100 Preoperative Full Spine X-Rays.
Global Spine Journal. 21925682231154543.
(2023). Short-term density forecasting of low-voltage load using Bernstein-polynomial normalizing flows.
IEEE Transactions on Smart Grid.
(2023). Visual Pitch and Roll Estimation For Inland Water Vessels.
IEEE International Conference on Robotics and Automation (ICRA). 1961-1967.
(2023). 140. Automated measurement technique for coronal parameters using a novel artificial intelligence algorithm: an independent validation study on 100 preoperative AP spine X-rays.
The Spine Journal. 22, S74.
(2022). Crowd Management in der Lehre.
Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 123-132.
(2022). Deep and interpretable regression models for ordinal outcomes.
Pattern Recognition. 122, 108263.
(2022). DeepDoubt - Improving uncertainty measures in machine learning to improve explainability and transparency.
2022 All-Hands-Meeting of the BMBF-funded AI Research Projects at Munich Center for Machine Learning. AHM2022_DeepDoubt.pdf (238.98 KB)
(2022). Fast and efficient image novelty detection based on mean-shifts.
Sensors | Unusual Behavior Detection Based on Machine Learning .
(2022). Fast and memory-efficient independent component analysis using Lie group techniques.
International Conference on Curves and Surfaces.
(2022). Image novelty detection based on mean-shift and typical set size.
21th International Conference on Image Analysis and Processing, ICIAP. ICIAP-mean-shift-novelty-detection-preprint.pdf (2.96 MB)
(2022). Large-scale independent component analysis by speeding up Lie group techniques.
International Conference on Acoustics, Speech, and Signal Processing, ICASSP. conference_101719.pdf (646.58 KB)
(2022). Mathematik mit digitalen Bildern sichtbar machen.
Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 133-145.
(2022). Targetless Lidar-camera registration using patch-wise mutual information.
International Conference on Information Fusion. mir_reg_patch.pdf (9.58 MB)
(2022).
(2022). Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations.
2021 International Conference on Data Mining Workshops (ICDMW). 398-404.
(2021). Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations.
2021 International Conference on Data Mining Workshops (ICDMW). 398–404.
(2021). Biologically-inspired vs. CNN texture representations in novelty detection.
Applications of Machine Learning 2021. 118430I. Spie2021.pdf (5.33 MB)
(2021).