Biblio

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Author [ Title(Asc)] Type Year
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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).  Where did I take that snapshot? Scene-based homing by image matching. Biol. Cybern.. 79, 191 – 202.PDF icon Franz et al._1998_Where did I take that snapshot Scene-based homing by image matching.pdf (488.99 KB)
Yovel, Y., Stilz P., Franz M. O., Boonman A., & Schnitzler H.-U. (2009).  What a plant sounds like: the statistics of vegetation echoes as received by echolocating bats. PLoS Comput. Biol.. 5, e1000429. doi:10.1371/journal.pcbi.1000429.PDF icon Yovel et al._2009_What a plant sounds like the statistics of vegetation echoes as received by echolocating bats.pdf (855.02 KB)
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.
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Franz, M. O., Hengstenberg R., & Krapp H. G. (1998).  VS-neurons as matched filters for self-motion-induced optic flow fields. (Elsner, N., & Wehner R., Ed.).{New Neuroethology on the Move}. II, 419.
Bohnet, D., & Vartziotis D. (2016).  Von der Symmetriegruppe des Dreiecks zur Glättung von industriellen Netzen. Die Basis der Vielfalt - 10. Tagung der DGfGG.
Franz, M. O. (2011).  Volterra and Wiener series. Scholarpedia. 6, 11307.
Yovel, Y., Melcón M. L., Franz M. O., Denzinger A., & Schnitzler H.-U. (2009).  The voice of bats: how greater mouse-eared bats recognize individuals based on their echolocation calls. PLoS Comput. Biol.. 5, e1000400:10.1371/journal.pcbi.1000400.PDF icon Yovel et al._2009_The voice of bats how greater mouse-eared bats recognize individuals based on their echolocation calls.pdf (458.53 KB)
Schall, M., Sacha D., Stein M., Franz M. O., & Keim D. A. (2018).  Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition. Visualization in Data Science (VDS at IEEE VIS) 2018. PDF icon Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition.pdf (1.03 MB)
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.
Danhof, M., Schneider T., Laube P., & Umlauf G. (2015).  A Virtual-Reality 3d-Laser-Scan Simulation. BW-CAR| SINCOM. 68.
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)
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)
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.
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Dürr, O., & Brandenburg A. (2012).  Using Community Structure for Complex Network Layout. arXiv preprint arXiv:1207.6282.
Franz, M. O., & Schölkopf B. (2006).  A unifying view of Wiener and Volterra theory and polynomial kernel regression. Neural Computation. 18, 3097 – 3118.PDF icon Franz, Schölkopf_2006_A Unifying View of Wiener and Volterra Theory and Polynomial Kernel Regression.pdf (165.97 KB)
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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)
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.
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)
Hörtling, S., Dold D., Dürr O., & Sick B. (2021).  Transformation models for flexible posteriors in variational bayes. arXiv preprint. 2106.00528.PDF icon 2106.00528.pdf (1.03 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)
Dürr, O. (2003).  Theoretical Studies of Relaxation and Ionic Transport in Polymers.
Umlauf, G. (2004).  A technique for verifying the smoothness of subdivision schemes. (Lucian, M.L., & Neamtu M., Ed.).Geometric Modeling and Computing: Seattle 2003. PDF icon subSchemes.pdf (110.4 KB)
Hermann, M., Griesser D., Gundel B., Dold D., Umlauf G., & Franz M. O. (2022).  Targetless Lidar-camera registration using patch-wise mutual information. International Conference on Information Fusion. PDF icon mir_reg_patch.pdf (9.58 MB)
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Franz, M. O., Yovel Y., Melcón M. L., Stilz P., & Schnitzler H.-U. (2012).  Systematische Merkmalsbewertung in komplexen Ultraschallsignalen mit Lernmaschinen. Informatik-Spektrum. 35, 348 – 353.PDF icon Franz et al._2011_Systematische Merkmalsbewertung in komplexen Ultraschallsignalen mit Lernmaschinen.pdf (899.32 KB)

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