Biblio

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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)
Lehner, B., Umlauf G., & Hamann B. (2008).  Video compression using data-dependent triangulations. (Xiao, Y., & E. Thij ten., Ed.).Computer Graphics and Visualization '08. PDF icon VideoComprTriang.pdf (177.45 KB)
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)
Lehner, B., Umlauf G., & Hamann B. (2007).  Survey of techniques for data-dependent triangulations. (Hagen, H., Hering-Bertram M., & Garth C., Ed.).GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets. PDF icon TriangColorImg.pdf (3.64 MB)
Lehner, B., Umlauf G., Hamann B., & Ustin S. (2006).  Topographic distance functions for interpolation of meteorological data. (Hagen, H., Kerren A., & Dannenmann P., Ed.).GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets. PDF icon TopoDistFunc.pdf (2.27 MB)
Lukic, Y., Vogt C., Dürr O., & Stadelmann T. (2016).  Speaker Identification and Clustering using Convolution Neural Networks. IEEE International workshop on Machine Learning for Signal Processing.
Lukic, Y. X., Vogt C., Dürr O., & Stadelmann T. (2017).  Learning embeddings for speaker clustering based on voice equality. Machine Learning for Signal Processing (MLSP), 2017 IEEE 27th International Workshop on. 1–6.PDF icon MLSP_2017.pdf (1.34 MB)
M
Mallot, H. A., Gillner S., Steck S. D., & Franz M. O. (1999).  Recognition-triggered response and the view-graph approach to spatial cognition. (Freksa, C., & Mark D. M., Ed.).{Spatial Information Theory - Cognitive and Computational Foundations of Geographic Information Science (COSIT 99)}. 1661, 367-380.
Mallot, H. A., Franz M. O., Schölkopf B., & Bülthoff H. H. (1997).  The view-graph approach to visual navigation and spatial memory. (Gerstner, W., Germond A., Hasler M., & Nicoud J.-D., Ed.).{Proc. of the 7th Intl. Conf. on Artificial Neural Networks (ICANN 97)}. 1327, 751 – 756.PDF icon Mallot et al._1997_The view-graph approach to visual navigation and spatial memory.pdf (212.16 KB)
McAuley, J. J., Caetano T. S., Smola A. J., & Franz M. O. (2006).  Learning high-order MRF priors of color images. {Proc. of the 23rd Intl. Conf. on Machine Learning (ICML 2006)}. 617–624.PDF icon McAuley et al._2006_Learning high-order MRF priors of color images.pdf (981.67 KB)
Meier, B. Bruno, Elezi I., Amirian M., Dürr O., & Stadelmann T. (2018).  Learning Neural Models for End-to-End Clustering. IAPR Workshop on Artificial Neural Networks in Pattern Recognition. 126–138.PDF icon ANNPR_2018a.pdf (3.43 MB)
Meier, B. Bruno, Stadelmann T., & Dürr O. (2018).  Learning to Cluster. PDF icon learning_to_cluster.pdf (1.82 MB)
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.
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Oliver, D., Frisch H., & Dieterich W. (2001).  Melt viscosities of lattice polymers using a Kramers potential treatment. J. Chem. Phys.. 115, 9042–9045.
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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.
Peters, J., & Umlauf G. (2000).  Gaussian and mean curvature of subdivision surfaces. (Cipolla, R., & Martin R., Ed.).The Mathematics of Surfaces IX. PDF icon SubCurvat.pdf (112.52 KB)
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)
Prautzsch, H., & Umlauf G. (1998).  A G^2 subdivision algorithm. Computing. 13, 217-224.PDF icon g2algorithm.pdf (196.14 KB)
Prautzsch, H., & Umlauf G. (1999).  Triangular G^2 splines. (Laurent, P.-L., Sablonniere P., & Schumaker L.L., Ed.).Curve and Surface Design. PDF icon TriG2Splines.pdf (393.87 KB)
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)
Prautzsch, H., & Umlauf G. (2006).  Parametrizations for triangular G^k spline surfaces of low degree. ACM Transactions on Graphics. 24, 1281-1293.PDF icon GkSplineSurf.pdf (539.25 KB)
Prautzsch, H., & Umlauf G. (1999).  Improved triangular subdivision schemes. (Wolter, F.-E., & Patrikalakis N.M., Ed.).Proceedings of the CGI '98. PDF icon TriSub.pdf (1.73 MB)
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Ramadane, M., & Bohnet D. (2025).  Dynamic Use-Phase Variability In IoT-Enabled Systems: A Simulation-Based Case Study Of Smart Thermostats. ECMS 2025 Proceedings edited by Marco Scarpa, Salvatore Cavalieri, Salvatore Serrano, Fabrizio De Vita. 711–717.
Ramadane, M., Meyer S., & Bohnet D. (2024).  Environmental Impact Assessment of IoT Devices: A Graph-based Approach. Procedia Computer Science. 236, 338–347.
Ramadane, M., & Bohnet D. (2026).  Preventing Parasitic Learning in Online Identification of Building RC Thermal Models: A Stochastic-Volatility Rao–Blackwellized Particle Filter.

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