Biblio

Export 121 results:
[ Author(Desc)] Title Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
G
Ginkel, I., & Umlauf G. (2007).  Tuning subdivision algorithms using constrained energy minimization. (Martin, R., Sabin M., & Winkler J., Ed.).Mathematics of Surfaces XII. PDF icon SubEnergyOpt.pdf (828.98 KB)
Ginkel, I., & Umlauf G. (2008).  Local energy-optimizing subdivision algorithms. Computer Aided Geometric Design. 25, 137-147.PDF icon OptSub.pdf (706.26 KB)
Ginkel, I., Peters J., & Umlauf G. (2007).  Normals of subdivision surfaces and their control polyhedra. Computer Aided Geometric Design. 24, 112-116.PDF icon SubSurfContrPoly.pdf (272.28 KB)
Ginkel, I., & Umlauf G. (2007).  Analyzing a generalized Loop subdivision scheme. Computing. 79, 353-363.PDF icon AnalyzeSubScheme.pdf (190.38 KB)
Griesser, D., Umlauf G., & Franz M. O. (2023).  Visual Pitch and Roll Estimation For Inland Water Vessels. IEEE International Conference on Robotics and Automation (ICRA). 1961-1967.
Griesser, D., Franz M. O., & Umlauf G. (2024).  Enhancing Inland Water Safety: The Lake Constance Obstacle Detection Benchmark. IEEE International Conference on Robotics and Automation (ICRA). 14808-14814.
Griesser, D., Dold D., Umlauf G., & Franz M. O. (2020).  CNN-Based Monocular 3D Ship Detection Using Inverse Perspective. Global Oceans.
Grunwald, M., Hermann M., Freiberg F., & Franz M. O. (2021).  Biologically-inspired vs. CNN texture representations in novelty detection. Applications of Machine Learning 2021. 118430I.PDF icon Spie2021.pdf (5.33 MB)
Grunwald, M., Laube P., Schall M., Umlauf G., & Franz M. O. (2017).  Radiometric calibration of digital cameras using neural networks. Optics and Photonics for Information Processing XI.
Grunwald, M., Hermann M., Freiberg F., & Franz M. O. (2018).  Optical Surface Detection: A novelty detection approach based on CNN-encoded features. SPIE Optics and Photonics. 10752 - 10752 - 13.PDF icon Spie2018.pdf (730 KB)
Grunwald, M., & Franz M. O. (2016).  Wahrnehmungsorientierte optische Inspektion von texturierten Oberflächen. INFORMATIK 2016, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik. 259, 1963–1968.
Grunwald, M., Müller J., Schall M., Laube P., Umlauf G., & Franz M. O. (2015).  Pixel-wise Hybrid Image Registration on Wood Decors. BW-CAR| SINCOM. 24.PDF icon Grunwald_2015_Pixel-wiseHybridImageRegistration.pdf (2.42 MB)
Grunwald, M., Gansloser J., & Franz M. O. (2016).  Radiometric calibration of digital cameras using sparse Gaussian processes. Workshop Farbbildverarbeitung.
H
Hake, F., Hermann M., Alkhatib H., Hesse C., Holste K., Umlauf G., et al. (2020).  Damage Detection for Port Infrastructure by Means of Machine-Learning-Algorithms. FIG Working Week 2020. PDF icon Fig2020.pdf (876.57 KB)
Hermann, M., Goldlücke B., & Franz M. O. (2022).  Image novelty detection based on mean-shift and typical set size. 21th International Conference on Image Analysis and Processing, ICIAP. PDF icon ICIAP-mean-shift-novelty-detection-preprint.pdf (2.96 MB)
Hermann, M., Madrid N., & Seepold R. (2017).  Detection of variations in holter ECG recordings based on dynamic cluster analysis. International Conference on Intelligent Decision Technologies.
Hermann, M., Griesser D., Gundel B., Dold D., Umlauf G., & Franz M. O. (2022).  Targetless Lidar-camera registration using patch-wise mutual information. International Conference on Information Fusion. PDF icon mir_reg_patch.pdf (9.58 MB)
Hermann, M., Umlauf G., Goldlücke B., & Franz M. O. (2023).  Incremental one-class learning using regularized null-space training for industrial defect detection. 16th International Conference on Machine Vision (ICMV).
Hermann, M., Umlauf G., Goldlücke B., & Franz M. O. (2022).  Fast and efficient image novelty detection based on mean-shifts. Sensors | Unusual Behavior Detection Based on Machine Learning .
Hermann, M., Umlauf G., & Franz M. O. (2022).  Large-scale independent component analysis by speeding up Lie group techniques. International Conference on Acoustics, Speech, and Signal Processing, ICASSP. PDF icon conference_101719.pdf (646.58 KB)
Hermann, M., Umlauf G., & Franz M. O. (2022).  Fast and memory-efficient independent component analysis using Lie group techniques. International Conference on Curves and Surfaces.
Hermann, M., Dold D., Umlauf G., & Dürr O. (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. PDF icon AHM2022_DeepDoubt.pdf (238.98 KB)
Herzog, L., Kook L., Götschi A., Petermann K., Hänsel M., Hamann J., et al. (2023).  Deep transformation models for functional outcome prediction after acute ischemic stroke. Biometrical Journal. 65, 2100379.
Herzog, L., Murina E., Dürr O., Wegener S., & Sick B. (2020).  Integrating uncertainty in deep neural networks for MRI based stroke analysis. Medical Image Analysis. 65, 101790.
Hoher, P., Baur T., Reuter J., Griesser D., Govaers F., & Koch W. (2024).  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.

Pages