Biblio

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2020
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)
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)
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)
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)
Kook, L., Herzog L., Hothorn T., Dürr O., & Sick B. (2020).  Deep and interpretable regression models for ordinal outcomes. arXiv preprint. 2010.08376.
Kook, L., Herzog L., Hothorn T., Dürr O., & Sick B. (2020).  Deep and interpretable regression models for ordinal outcomes. arXiv preprint. 2010.08376.
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.
Kook, L., Herzog L., Hothorn T., Dürr O., & Sick B. (2020).  Ordinal neural network transformation models: deep and interpretable regression models for ordinal outcomes. arXiv e-prints. 2010.08376.
Kook, L., Herzog L., Hothorn T., Dürr O., & Sick B. (2020).  Ordinal neural network transformation models: deep and interpretable regression models for ordinal outcomes. arXiv e-prints. 2010.08376.
2017
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.
2015
Denker, K., Hamann B., & Umlauf G. (2015).  On-line CAD Reconstruction with Accumulated Means of Local Geometric Properties. (Boissonnat, J-D., Cohen A., Gibaru O., Gout C., Lyche T., Mazure M-L., et al., Ed.).Curves and Surfaces, 8th International Conference, Paris 2014. 181-201.PDF icon OnlineCADReconst.pdf (3.18 MB)
2013
Denker, K., Hagel D., Raible J., Umlauf G., & Hamann B. (2013).  On-line reconstruction of CAD geometry. International Conference on 3d Vision. PDF icon OnlineReconstruction.pdf (392.38 KB)
Denker, K., Hagel D., Raible J., Umlauf G., & Hamann B. (2013).  On-line reconstruction of CAD geometry. International Conference on 3d Vision. PDF icon OnlineReconstruction.pdf (392.38 KB)
2012
Bender, C., Denker K., Friedrich M., Hirt K., & Umlauf G. (2012).  A hand-held laser scanner based on multi-camera stereo-matching. Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop. PDF icon LaserScannerStereoMatching.pdf (584.47 KB)
2011
Burkhart, D., Hamann B., & Umlauf G. (2011).  Finite element analysis for linear elastic solids based on subdivision schemes. Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop. PDF icon FEALinearElasticSolids.pdf (2.35 MB)
2010
Burkhart, D., Hamann B., & Umlauf G. (2010).  Adaptive and feature-preserving subdivision for high-quality tetrahedral meshes. Computer Graphics Forum. 29, 117-127.PDF icon AdaptiveSubTetraMeshes.pdf (1022.53 KB)
Burkhart, D., Hamann B., & Umlauf G. (2010).  Adaptive tetrahedral subdivision for finite element analysis. (.N., N., Ed.).Computer Graphics International, Singapore 2010. PDF icon TetraSubFEA.pdf (3.43 MB)
Lehner, B., Hamann B., & Umlauf G. (2010).  Generalized swap operation for tetrahedrizations. (Hagen, H., Ed.).Scientific Visualization: Advanced Concepts. PDF icon SwapTetrahed.pdf (333.85 KB)

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