Biblio

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Book
Meier, B. Bruno, Stadelmann T., & Dürr O. (2018).  Learning to Cluster. PDF icon learning_to_cluster.pdf (1.82 MB)
Dürr, O., Sick B., & Murina E. (2020).  Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability.
Dürr, O., Sick B., & Murina E. (2020).  Probabilistic deep learning: With python, keras and tensorflow probability.
Book Chapter
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.
Franz, M. O., Stürzl W., Hübner W., & Mallot H. A. (2008).  A robot system for biomimetic navigation - from snapshots to metric embeddings of view graphs. (Yeap, A. W., & Jefferies M., Ed.).{Robotics and Cognitive Approaches to Spatial Mapping}. 38, 297–314.
Conference Paper
Franz, M. O., Schölkopf B., Mallot H. A., & Bülthoff H. H. (1996).  Aktives Erwerben eines Ansichtsgraphen zur diskreten Repräsentation offener Umwelten. (Thielscher, M., & Bornscheuer S.-E., Ed.).Fortschritte der {Künstlichen Intelligenz}. 92.PDF icon Franz et al._1996_Aktives Erwerben eines Ansichtsgraphen zur diskreten Repräsentation offener Umwelten.pdf (63.1 KB)
Seepold, R., Dermati C., Kostka A., Pfeil L., Lange R., Hermann M., et al. (2016).  Analyzing environmental conditions and vital signs to increase healthy living. Mobile Networks for Biometric Data Analysis.
Casanova, R., Murina E., Haberecker M., Honcharova-Biletska H., Vrugt B., Dürr O., et al. (2018).  Automatic classification of non-small cell lung cancer histologic sub-types by deep learning. VIRCHOWS ARCHIV. 108-108.
Yovel, Y., Stilz P., Melcón M. L., Franz M. O., & Schnitzler H.-U. (2008).  Bats can use echolocation calls for individual recognition. {Proc. Sensory coding and the natural environment 2008}.
Franz, M. O., Neumann T. R., Plagge M., Mallot H. A., & Zell A. (1999).  Can fly tangential neurons be used to estimate self-motion?. (Willshaw, D., & Murray A., Ed.).{Proc. of the 9th Intl. Conf. on Artificial Neural Networks (ICANN 1999)}. CP 470, 994-999.PDF icon Franz et al._1999_Can fly tangential neurons be used to estimate self-motion.pdf (170.74 KB)
Franz, M. O., Neumann T. R., Plagge M., Mallot H. A., & Zell A. (1999).  Can fly tangential neurons be used to estimate self-motion?. (Willshaw, D., & Murray A., Ed.).{Proc. of the 9th Intl. Conf. on Artificial Neural Networks (ICANN 1999)}. CP 470, 994-999.PDF icon Franz et al._1999_Can fly tangential neurons be used to estimate self-motion.pdf (170.74 KB)
Bakır, G. H., Ilg W., Franz M. O., & Giese M. (2003).  Constraints measures and reproduction of style in robot imitation learning. (Bülthoff, H. H., Gegenfurtner K. R., Mallot H. A., Ulrich R., & Wichmann F. A., Ed.).{Proc. 6. Tübinger Wahrnehmungskonferenz (TWK 2003)}. 70.
Ginkel, I., & Umlauf G. (2006).  Controlling a subdivision tuning method. (Cohen, A., Merrien J.-L., & Schumaker L.L., Ed.).Curve and Surface Fitting. PDF icon SubTuning.pdf (553.79 KB)
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.
Bobach, T., Farin G., Hansford D., & Umlauf G. (2007).  Discrete harmonic functions from local coordinates. (Martin, R., Sabin M., & Winkler J., Ed.).Mathematics of Surfaces XII. PDF icon HarmonicFunc.pdf (835.96 KB)
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.
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.
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)
Bobach, T., Constantiniu A., Steinmann P., & Umlauf G. (2010).  Geometric properties of the adaptice Delaunay tessellation. (Dæhlen, M., Floater M.S., Lyche T., Merrien J.-L., Morken K., & Schumaker L.L., Ed.).Mathematical Methods of Curves and Surfaces, Tondsberg 2008. PDF icon ADTProperties.pdf (335.14 KB)
Bobach, T., Constantiniu A., Steinmann P., & Umlauf G. (2010).  Geometric properties of the adaptice Delaunay tessellation. (Dæhlen, M., Floater M.S., Lyche T., Merrien J.-L., Morken K., & Schumaker L.L., Ed.).Mathematical Methods of Curves and Surfaces, Tondsberg 2008. PDF icon ADTProperties.pdf (335.14 KB)
Ilg, W., Bakır G. H., Franz M. O., & Giese M. A. (2003).  Hierarchical spatio-temporal morphable models for representation of complex movements for imitation learning. (Nunes, U., de Almeida A., Bejczy A., Kosuge K., & Machado J., Ed.).{Proc. of the 11th International Conference on Advanced Robotics}. 2, 453–458.PDF icon Ilg et al._2003_Hierarchical spatio-temporal morphable models for representation of complex movements for imitation learning.pdf (716.98 KB)
Laube, P., Michael G., Franz M. O., & Umlauf G. (2018).  Image Inpainting for High-Resolution Textures using CNN Texture Synthesis. Computer Graphics & Visual Computing (CGVC). PDF icon gcvc18.pdf (5.73 MB)
Franz, M. O., Macke J. H., Saleem A., & Schultz S. R. (2007).  Implicit Wiener series for estimating nonlinear receptive fields. {Proc. 31st Göttingen Neurobiolgy Conf.}. 1199.
Sinz, F., & Franz M. O. (2004).  Learning depth. (Bülthoff, H. H., Mallot H. A., Ulrich R., & Wichmann F. A., Ed.).{Proc. 7. Tübinger Wahrnehmungskonferenz (TWK 2004)}. 68.PDF icon Sinz et al Learning depth 2004.pdf (197 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)

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