Publications of J Eichhorn
All genres
Journal Article (1)
1.
Journal Article
5 (4), pp. 1 - 16 (2009)
Natural Image Coding in V1: How Much Use is Orientation Selectivity? PLoS Computational Biology Conference Paper (2)
2.
Conference Paper
: The 2005 PASCAL Visual Object Classes Challenge. In: Machine Learning Challenges: Evaluating Predictive Uncertainty, Visual Object Classification, and Recognising Tectual Entailment First PASCAL Machine Learning Challenges Workshop, MLCW 2005, Southampton, UK, April 11-13, 2005, pp. 117 - 176 (Eds. Quiñonero-Candela, J.; Dagan, I.; Magnini, B.; d’Alché-Buc, F.). First PASCAL Machine Learning Challenges Workshop (MLCW 2005), Southampton, UK, April 11, 2005 - April 13, 2005. Springer, Berlin (2006)
3.
Conference Paper
Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, December 08, 2003 - December 13, 2003. MIT Press, Cambridge, MA, USA (2004)
Prediction on Spike Data Using Kernel Algorithms. In: Advances in Neural Information Processing Systems 16: Proceedings of the 2003 Conference, pp. 1367 - 1374 (Eds. Thrun, S.; Saul, L.; Meeting Abstract (1)
4.
Meeting Abstract
Linking V1 receptive field properties to optimal coding principles. In 37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007), 768.6. 37th Annual Meeting of the Society for Neuroscience (Neuroscience 2007), San Diego, CA, USA, November 03, 2007 - November 07, 2007. (2007)
Talk (1)
5.
Talk
Grundlagen von Support Vector Maschinen und Anwendungen in der Bildverarbeitung. Workshop: Numerical, Statistical and Discrete Methods in Image Processing, München, Germany (2004)
Thesis - PhD (1)
6.
Thesis - PhD
Applications of Kernel Machines to Structured Data. Dissertation, 157 pp., Technische Universität Berlin, Berlin, Germany (2007)
Thesis - Diploma (1)
7.
Thesis - Diploma
Variationsverfahren zur Untersuchung von Grundzustandseigenschaften des Ein-Band Hubbard-Modells. Diploma, Technische Universität Dresden, Dresden, Germany (2001)
Report (2)
8.
Report
Maximum-Margin Feature Combination for Detection and Categorization. Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2005), 8 pp.
9.
Report
137). Max Planck Institute for Biological Cybernetics, Tübingen, Germany (2004), 9 pp.
Object categorization with SVM: kernels for local features (Technical Report of the Max Planck Institute for Biological Cybernetics,