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Inhalt des Dokuments



Schmitt, S., Evers, J.-F., Duch, C., Scholz, M. and Obermayer, K. (2004). New Methods for the Computer-Assisted 3D Reconstruction of Neurons from Confocal Image Stacks. Neuroimage, 23, 1283 – 1298.

Schwetz, I., Gruhler, G. and Obermayer, K. (2004). Stationarity of Speech Radiation: Consequences for Linear Multichannel Filtering. IEEE Transactions on Speech and Audio Processing ., 12, 460 – 467.

Seo, S. and Obermayer, K. (2004). Self-Organizing Maps and Clustering Methods for Matrix Data. Neural Networks Special Issue, 17, 1211 – 1229.

Adiloglu, K. and Obermayer, K. (2004). An Evolutionary Approximation of the Similarity Neighborhood Model for the Melodic Segmentation. Proceedings of the 4th Interantional Conference on Understanding and Creating Music, Caserta, 23 – 27.,

Bartsch, H., Hochreiter, S. and Obermayer, K. (2004). Learning Quadratic Forms by Density Estimation and its Application to Image Coding. Neurocomputing

Vollgraf, R., Scholz, M., Meinertzhagen, I. and Obermayer, K. (2004). Nonlinear Filtering of Electron Micrographs by Means of Support Vector Regression. Advances in Neural Information Processing Systems 16. MIT Press, 717 – 724.,

Garg, A., Bhaumik, B. and Obermayer, K. (2004). Development of a Simple Cell Preceptive Field Structure: A Model Based on Hetero-Synaptic Interactions. Lecture Notes in Computer Science. Springer-Verlag, 64 – 68.,


Hochreiter, S., Mozer, M. and Obermayer, K. (2003). Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems. Advances in Neural Information Processing Systems 15. MIT Press, 561 – 568.,

Hochreiter, S. and Obermayer, K. (2003). Feature Selection and Classification on Matrix Data: From Large Margins To Small Covering Numbers. Advances in Neural Information Processing Systems 15. MIT Press, 913 – 920.,

Hochreiter, S. and Obermayer, K. (2003). Classification and Feature Selection on Matrix Data with Application to Gene-Expression Analysis. Proceedings of the International Statistical Institute, (1 – 4).,

Mohr, J., Hess, A., Scholz, M. and Obermayer, K. (2003). Segmentation of 2 1/2 D Brain Image Stacks with Automatic Extraction and Visualization of Functional Information. Proceedings of the IEEE International Conference of Image Processing - ICIP03, 1089 – 1092.,

Pielot, R., Scholz, M., Obermayer, K., Scheich, H., Gundelfinger, E. and Hess, A. (2003). A New Point-Based Warping Method for Enhanced and Simplified Analysis of Functional Brain Image Data. Neuroimage, 19, 1716 – 1729.

Schwabe, L. and Obermayer, K. (2003). Modelling the Adaptive Visual System: A Survey of Principled Approaches. Neur. Netw., 16, 1353 – 1371.

Seo, S., Bode, M. and Obermayer, K. (2003). Soft Nearest Prototype Classification. IEEE Transactions on Neural Networks, 14, 390 – 398.

Seo, S. and Obermayer, K. (2003). Soft Learning Vector Quantization. Neural Computation, 15, 1589 – 1604.

Dima, A., Scholz, M. and Obermayer, K. (2003). Automatic Segmentation and Skeletonization of Neurons from Confocal Microscopy Images Based on the 3-D Wavelet Transform. IEEE TRANSACTIONS ON IMAGE PROCESSING, 11, 790-801.

Bartsch, H. and Obermayer, K. (2003). Second Order Statistics of Natural Images. Neurocomputing, 52-54, 541 – 546.

Wenning, G. and Obermayer, K. (2003). Activity Driven Adaptive Stochastic Resonance. Physical Review Letters, 90, 120602.

Cuadros-Vargas, E., Romero, R. and Obermayer, K. (2003). Speeding up Algorithms of the SOM Family for Large and High Dimensional Databases. Proceedings WSOM, 167 – 172.,

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