Biblio

Export 122 results:
Author Title [ Type(Desc)] Year
Journal Article
Berlin, C., Adomeit S., Grover P., Dreischarf M., Dürr O., & Obid P. (2022).  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.
Denker, K., & Umlauf G. (2011).  An accurate real-time multi-camera matching on the GPU for 3d reconstruction. Journal of WSCG. 19, 9-16.PDF icon RealTimeMultiCamera.pdf (770.39 KB)
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)
Constantiniu, A., Steinmann P., Bobach T., Farin G., & Umlauf G. (2008).  The adaptive Delaunay tesselation: A neighborhood covering meshing technique. Computational Mechanics. 42, 655-669.PDF icon AdaptDelTess.pdf (1.33 MB)
Ginkel, I., & Umlauf G. (2007).  Analyzing a generalized Loop subdivision scheme. Computing. 79, 353-363.PDF icon AnalyzeSubScheme.pdf (190.38 KB)
Umlauf, G. (2000).  Analyzing the characteristic map of triangular subdivision schemes. Constructive Approximation. 16, 145-155.PDF icon LoopCharMap.pdf (431.79 KB)
Dürr, O., Fan P-Y., & Yin Z-X. (2023).  Bayesian Calibration of MEMS Accelerometers. IEEE Sensors Journal.
Bohnet, D. (2013).  Codimension one partially hyperbolic diffeomorphisms with a uniformly compact center foliation. J. Mod. Dyn.. 7(4), 
Peters, J., & Umlauf G. (2001).  Computing curvature bounds for bounded curvature subdivision. Computer Aided Geometric Design. 18, 455-462.PDF icon CurvatBnd.pdf (179.48 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. (2022).  Deep and interpretable regression models for ordinal outcomes. Pattern Recognition. 122, 108263.
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.
Pearse, G. D., Tan A. Y. S., Watt M. S., Franz M. O., & Dash J. P. (2020).  Detecting and mapping tree seedlings in UAV imagery using convolutional neural networks and field-verified data. ISPRS Journal of Photogrammetry and Remote Sensing. 168, 156 - 169.
Siegismund, D., Tolkachev V., Heyse S., Sick B., Dürr O., & Steigele S. (2018).  Developing deep learning applications for life science and pharma industry. Drug research. 68, 305–310.
Bohnet, D., & Vartziotis D. (2016).  Existence of an attractor for a geometric tetrahedron transformation. Differential Geom. Appl.. 49,
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 .
Bohnet, D., & Vartziotis D. (2018).  Fractal Curves from Prime Trigonometric Series. Fractal Fract.. 2(2), 
Prautzsch, H., & Umlauf G. (2000).  A G^1 and a G^2 subdivision scheme for trinagular nets. International Journal on Shape Modelling. 6, 21-35.PDF icon G1G2TriAlgo.pdf (2.61 MB)

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