Biblio

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H
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)
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Grunwald, M., & Franz M. O. (2016).  Wahrnehmungsorientierte optische Inspektion von texturierten Oberflächen. INFORMATIK 2016, Lecture Notes in Informatics (LNI), Gesellschaft für Informatik. 259, 1963–1968.
Grunwald, M., Hermann M., Freiberg F., & Franz M. O. (2021).  Biologically-inspired vs. CNN texture representations in novelty detection. Applications of Machine Learning 2021. 118430I.PDF icon Spie2021.pdf (5.33 MB)
Grunwald, M., Müller J., Schall M., Laube P., Umlauf G., & Franz M. O. (2015).  Pixel-wise Hybrid Image Registration on Wood Decors. BW-CAR| SINCOM. 24.PDF icon Grunwald_2015_Pixel-wiseHybridImageRegistration.pdf (2.42 MB)
Grunwald, M., Hermann M., Freiberg F., & Franz M. O. (2018).  Optical Surface Detection: A novelty detection approach based on CNN-encoded features. SPIE Optics and Photonics. 10752 - 10752 - 13.PDF icon Spie2018.pdf (730 KB)
Grunwald, M., Gansloser J., & Franz M. O. (2016).  Radiometric calibration of digital cameras using sparse Gaussian processes. Workshop Farbbildverarbeitung.
Grunwald, M., Laube P., Schall M., Umlauf G., & Franz M. O. (2017).  Radiometric calibration of digital cameras using neural networks. Optics and Photonics for Information Processing XI.
Griesser, D., Umlauf G., & Franz M. O. (2023).  Visual Pitch and Roll Estimation For Inland Water Vessels. IEEE International Conference on Robotics and Automation (ICRA). 1961-1967.
Griesser, D., Dold D., Umlauf G., & Franz M. O. (2020).  CNN-Based Monocular 3D Ship Detection Using Inverse Perspective. Global Oceans.
Ginkel, I., Peters J., & Umlauf G. (2005).  On normals and control nets. (Martin, R., Bez H., & M. 233-239 S. pages =, Ed.).Mathematics of Surfaces XI. PDF icon NormalsControlNets.pdf (117.42 KB)
Ginkel, I., & Umlauf G. (2006).  Loop subdivision with curvature control. (Polthier, K., & Sheffer A., Ed.).Eurographics Symposium on Geometry Processing. PDF icon LoopSubCurv.pdf (6.03 MB)
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)
Ginkel, I., & Umlauf G. (2008).  Symmetry of shape charts. Computer Aided Geometric Design. 25, 131-136.PDF icon Symmetry.pdf (483.24 KB)
Ginkel, I., & Umlauf G. (2007).  Tuning subdivision algorithms using constrained energy minimization. (Martin, R., Sabin M., & Winkler J., Ed.).Mathematics of Surfaces XII. PDF icon SubEnergyOpt.pdf (828.98 KB)
Ginkel, I., & Umlauf G. (2008).  Local energy-optimizing subdivision algorithms. Computer Aided Geometric Design. 25, 137-147.PDF icon OptSub.pdf (706.26 KB)
Ginkel, I., Peters J., & Umlauf G. (2007).  Normals of subdivision surfaces and their control polyhedra. Computer Aided Geometric Design. 24, 112-116.PDF icon SubSurfContrPoly.pdf (272.28 KB)
Ginkel, I., & Umlauf G. (2007).  Analyzing a generalized Loop subdivision scheme. Computing. 79, 353-363.PDF icon AnalyzeSubScheme.pdf (190.38 KB)
F
Franzini, A., Baty F., Macovei I. I., Dürr O., Droege C., Betticher D., et al. (2015).  Gene expression signatures predictive of bevacizumab/erlotinib therapeutic benefit in advanced non-squamous non-small cell lung cancer patients (SAKK 19/05 trial). Clinical Cancer Research. clincanres––3135.
Franzini, A., Dürr O., Baty F., & Brutsche M. (2014).  Tumor-associated stromal gene expression signatures predict therapeutic response to erlotinib/bevacizumab in non-small cell lung cancer (NSCLC). European Respiratory Journal. 44, P821.
Franzini, A., Dürr O., Baty F., Hosang J., & Brutsche M. H. (2014).  In Silico Identification of Cell-type-specific Compartmental Gene Expression Signatures with Predictive Value for Response to Erlotinib/bevacizumab Therapy in Non-small Cell Lung Cancer (nsclc). Respiration. 87, 562.
Franz, M. O., Schölkopf B., Mallot H. A., Bülthoff H. H., & Zell A. (1998).  Navigation mit Schnappschüssen.. (Levi, P., Ahlers R.-J., May F., & Schanz M., Ed.).{Mustererkennung 1998. Proc. of the 20th DAGM-Symposium}. 412-428.PDF icon Franz et al._1998_Navigation mit Schnappschüssen.pdf (300.5 KB)
Franz, M. O., & Krapp H. G. (2000).  Wide-field, motion-sensitive neurons and matched filters for optic flow fields. Biol. Cybern.. 83, 185 – 197.PDF icon Franz, Krapp_2000_Wide-field, motion-sensitive neurons and matched filters for optic flow fields.pdf (261.7 KB)
Franz, M. O., Schölkopf B., Mallot H. A., & Bülthoff H. H. (1998).  Learning view graphs for robot navigation. Autonomous Robots. 5, 111 – 125.PDF icon Franz et al._1998_Learning View Graphs for Robot Navigation.pdf (1.26 MB)
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.
Franz, M. O. (2003).  Robots with cognition?. (Bülthoff, H. H., Gegenfurtner K. R., Mallot H. A., Ulrich R., & Wichmann F. A., Ed.).{Proc. 6. Tübinger Wahrnehmungskonferenz (TWK 2003)}.

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