Biblio
Deep transformation models for functional outcome prediction after acute ischemic stroke.
Biometrical Journal. 65, 2100379.
(2023). Deep probabilistic modelling for energy forecasting.
Poster_Deep probabilistic modelling for energy forecasting TTT.pdf (839.27 KB)
(2023). Deep Learning Parametrization for B-Spline Curve Approximation.
2018 International Conference on 3D Vision (3DV). 691–699. 0109.pdf (675.91 KB)
(2018). Deep Learning on a Raspberry Pi for Real Time Face Recognition..
Eurographics (Posters). 11–12.
(2015). Deep and interpretable regression models for ordinal outcomes.
arXiv preprint. 2010.08376.
(2020). Deep and interpretable regression models for ordinal outcomes.
Pattern Recognition. 122, 108263.
(2022). Damage Detection for Port Infrastructure by Means of Machine-Learning-Algorithms.
FIG Working Week 2020. Fig2020.pdf (876.57 KB)
(2020). Crowd Management in der Lehre.
Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 123-132.
(2022). Coupled ion and network dynamics in polymer electrolytes: Monte Carlo study of a lattice model.
The Journal of chemical physics. 121, 12732–12739.
(2004). Controlling a subdivision tuning method.
(Cohen, A., Merrien J.-L., & Schumaker L.L., Ed.).Curve and Surface Fitting. SubTuning.pdf (553.79 KB)
(2006). 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.
(2003). A concept for a multi-spectral snap-shot camera based on single-chip RGB sensor.
Forum Bildverarbeitung. Poster.
(2018). Computing curvature bounds for bounded curvature subdivision.
Computer Aided Geometric Design. 18, 455-462. CurvatBnd.pdf (179.48 KB)
(2001). Comparison of Voronoi based scatterd data interpolation schemes.
(Villanueva, J.J., Ed.).Proceedings of the Internationl Conference on Visualization, Imaging and Image Processing. VoronoiInterp.pdf (4.63 MB)
(2006). A compact high-performance frequency reference for space applications.
{29th Intl. Symposium on Space Technology and Science (ISTS 2013), Nagoya (Japan)}. Schuldt et al._2013_A Compact High-Performance Frequency Reference for Space Applications.pdf (369.85 KB)
(2013). Codimension one partially hyperbolic diffeomorphisms with a uniformly compact center foliation.
J. Mod. Dyn.. 7(4),
(2013). CNN-Based Monocular 3D Ship Detection Using Inverse Perspective.
Global Oceans.
(2020). Charge Transport in Polymer Ion Conductors: a Monte Carlo Study.
arXiv preprint cond-mat/0106197.
(2001). Center-surround patterns emerge as optimal predictors for human saccade targets.
J. of Vision. 9, 1–15. Kienzle, Franz, Schölkopf_2009_Center-surround patterns emerge as optimal predictors for human saccade targets.pdf (900.5 KB)
(2009). Center-surround filters emerge from optimizing predictivity in a free-viewing task.
{Proc. of the Computational and Systems Neuroscience Meeting 2007 (COSYNE 2007)}.
(2007). Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering.
IAPR Workshop on Artificial Neural Networks in Pattern Recognition. 333–345. ANNPR_2018b.pdf (692.47 KB)
(2018). 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. Franz et al._1999_Can fly tangential neurons be used to estimate self-motion.pdf (170.74 KB)
(1999).
(2019).
Biomimetic robot navigation.
Robotics and Autonomous Systems. 30, 133 – 153. Franz, Mallot_2000_Biomimetic robot navigation.pdf (171.77 KB)
(2000). Biologically-inspired vs. CNN texture representations in novelty detection.
Applications of Machine Learning 2021. 118430I. Spie2021.pdf (5.33 MB)
(2021).