Biblio
Export 20 results:
[ Author] Title Type Year Filters: First Letter Of Title is I [Clear All Filters]
Implicit Wiener series analysis of epileptic seizure recordings..
{Ann. Intl. Conf. of the IEEE Engineering in Medicine and Biology Society}. 5304–5307. Barbero et al._2009_Implicit Wiener series analysis of epileptic seizure recordings.pdf (327.26 KB)
(2009). Issues and implementation of C^1 and C^2 natural neighbor interpolation.
(G. al., B. et, Ed.).Advances in Visual Computing. Part II. C1C2NeighborInterp.pdf (3.87 MB)
(2006). Iso-geometric analysis based on Catmull-Clark solid subdivision.
Computer Graphics Forum. 29, 1575-1784. IsoCatmullClarkSub.pdf (3.69 MB)
(2010). Implicit Wiener series for estimating nonlinear receptive fields.
{Proc. 31st Göttingen Neurobiolgy Conf.}. 1199.
(2007). Insect-inspired estimation of self-motion.
(Bülthoff, H. H., Lee S.-W., Poggio T. A., & Wallraven C., Ed.).{Proc. 2nd Workshop on Biologically Motivated Computer Vision (BMCV 2002)}. 2525, 171-180. Franz, Chahl_2002_Insect-inspired estimation of self-motion.pdf (274.5 KB)
(2002). Implicit Volterra and Wiener series for higher-order image analysis.
{Advances in Data Analysis 30th Ann. Conf. German Classification Society}. 60.
(2006). Insect-inspired estimation of egomotion..
Neural Computation. 16, 2245–60.
(2004). Implicit Wiener series for capturing higher-order interactions in images.
(Olshausen, B. A., & Lewicki M., Ed.).{Proc. Sensory Coding and the Natural Environment 2004}.
(2004). Implicit estimation of Wiener series.
(Barros, A., Principe J. C., Larsen J., Adali T., & Douglas S., Ed.).{Machine Learning for Signal Processing XIV, Proc. 2004 IEEE Signal Processing Society Workshop}. 735–744. Franz, Schölkopf_2004_Implicit estimation of Wiener series.pdf (191.86 KB)
(2004).
(2014). Image novelty detection based on mean-shift and typical set size.
21th International Conference on Image Analysis and Processing, ICIAP. ICIAP-mean-shift-novelty-detection-preprint.pdf (2.96 MB)
(2022). Incremental one-class learning using regularized null-space training for industrial defect detection.
16th International Conference on Machine Vision (ICMV).
(2023). Integrating uncertainty in deep neural networks for MRI based stroke analysis.
Medical Image Analysis. 65, 101790.
(2020). Iterative kernel principal component analysis for image modeling.
IEEE Trans. PAMI. 27, 1351 – 1366. Kim, Franz, Schölkopf_2005_Iterative Kernel Principal Component Analysis for Image Modeling.pdf (1.98 MB)
(2005). Image Inpainting for High-Resolution Textures using CNN Texture Synthesis.
Computer Graphics & Visual Computing (CGVC). gcvc18.pdf (5.73 MB)
(2018). Image Compression Using Data-Dependent Triangulations.
(al., G. Bebis et, Ed.).Advances in Visual Computing. ImgCompression.pdf (3.75 MB)
(2007). Improved triangular subdivision schemes.
(Wolter, F.-E., & Patrikalakis N.M., Ed.).Proceedings of the CGI '98. TriSub.pdf (1.73 MB)
(1999). Increasing robustness of handwriting recognition using character n-gram decoding on large lexica.
12th IAPR International Workshop on Document Analysis Systems. Schall et al_2016_Increasing robustness of handwriting recognition using character n-gram decoding on large lexica.pdf (440.82 KB)
(2016). Improving gradient-based LSTM training for offline handwriting recognition by careful selection of the optimization method.
Conference: BW-CAR Symposium on Information and Communication Systems (SInCom). 2016-12 Improving gradient-based LSTM training for offline handwriting recognition by careful selection of the optimization method.pdf (803.54 KB)
(2016). The influence of the image basis on modeling and steganalysis performance.
(Böhme, R., Fong P.W.L., & Safavi-Naini R., Ed.).{Proc. 12th Intl. Conf. on Information Hiding (IH-2010)}. 133–144. Schwamberger et al._2010_The Influence of the Image Basis on Modeling and Steganalysis Performance.pdf (392.83 KB)
(2010).