Biblio

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1
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.
C
Axthelm, R., Luppold S., & Moroff M. (2022).  Crowd Management in der Lehre. Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 123-132.
D
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)
Dold, D., Arpogaus M., & Dürr O. (2023).  Deep probabilistic modelling for energy forecasting. PDF icon Poster_Deep probabilistic modelling for energy forecasting TTT.pdf (839.27 KB)
E
Middendorf, L., Mühlbauer F., Umlauf G., & Bobda C. (2007).  Embedded vertex shader in FPGA. (A. al., R. et, Ed.).Embedded System Design: Topics, Techniques and Trends.
F
Axthelm, R. (2016).  Finite Element Simulation of a Macroscopic Model for Pedestrian Flow. Traffic and Granular Flow. 10.1007/978-3-319-33482-0_30, 233–240.
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Lehner, B., Umlauf G., & Hamann B. (2007).  Image Compression Using Data-Dependent Triangulations. (al., G. Bebis et, Ed.).Advances in Visual Computing. PDF icon ImgCompression.pdf (3.75 MB)
Bobach, T., Bertram M., & Umlauf G. (2006).  Issues and implementation of C^1 and C^2 natural neighbor interpolation. (G. al., B. et, Ed.).Advances in Visual Computing. Part II. PDF icon C1C2NeighborInterp.pdf (3.87 MB)
M
Axthelm, R. (2022).  Mathematik mit digitalen Bildern sichtbar machen. Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 133-145.
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Berlin, C., Adomeit S., Grover P., Dreischarf M., Halm H., Dürr O., et al. (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.
Axthelm, R. (2007).  Numerische Simulation von Zwei-Phasen Strömungen mit inkompressiblen Navier-Stokes Gleichungen und freiem Kapillarrand. Fakultät für Mathematik und Physik .
P
Arpogaus, M., Voß M., Sick B., Nigge-Uricher M., & Dürr O. (2021).  Probabilistic Short-Term Low-Voltage Load Forecasting using Bernstein-Polynomial Normalizing Flows. ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26, 2021, virtual. PDF icon Arpogaus2021_Probabilistic_Forecasting.pdf (427.35 KB)
Arpogaus, M., Voß M., Sick B., Nigge-Uricher M., & Dürr O. (2021).  Probabilistic short-term low-voltage load forecasting using bernstein-polynomial normalizing flows. ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26, 2021, virtual.
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Arpogaus, M., Voss M., Sick B., Nigge-Uricher M., & Dürr O. (2023).  Short-term density forecasting of low-voltage load using Bernstein-polynomial normalizing flows. IEEE Transactions on Smart Grid.
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Adomeit, S., Berlin C., Grover P., Dreischarf M., Halm H., Dürr O., et al. (2022).  Validation study of an algorithm based on artificial intelligence for automated computation of coronal parameters on preoperative AP X-rays. Brain and Spine. 2, 101156.