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TU Berlin

Inhalt des Dokuments

All Publications

Jain, B. and Obermayer, K. (2009). Bimal: Bipartite Matching Alignment for the Contact Map Overlap Problem. 2009 International Joint Conference on Neural Networks. IEEE, 1394 – 1400.,10.1109/IJCNN.2009.5178901


Jain, B. and Obermayer, K. (2009). Algorithms for the Sample Mean of Graphs. Lecture Notes in Computer Science, 351 – 359.,


Jain, B., Srinivasan, S. D., Tissen, A. and Obermayer, K. (2010). Learning Graph Quantization. Structural, Syntactic, and Statistical Pattern Recognition. Springer Berlin Heidelberg, 109 – 118.,10.1007/978-3-642-14980-1_10


Jain, B., Stehr, H., Lappe, M. and Obermayer, K. (2009). Multiple Alignment of Contact Maps. 2009 International Joint Conference on Neural Networks. IEEE, 1401 – 1406.,10.1109/IJCNN.2009.5178907


Jain, B. and Obermayer, K. (2008). On the Sample Mean of Graphs. 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence). IEEE, 993 – 1000.,10.1109/IJCNN.2008.4633920


Kim, H., Obermayer, K., Bode, M. and Ruswisch, D. (2001). A 1.2KBPS Speech Codec Using Spectral Vector Quantization of Differential Feature Vectors. Proceedings ICSP, 304.,


Kim, H., Obermayer, K., Bode, M. and Ruwisch, D. (2001). Efficient Speech Enhancement by Diffusive Gain Factors (DGF). Proc. Eurospeech 2001, 1867 – 1870.,


Kim, H., Obermayer, K., Bode, M. and Ruwisch, D. (2001). Real-Time Noise Suppression Based on Diffusive Gain Factors. Proceedings ICSP,


Kim, H., Obermayer, K., Bode, M. and Ruwisch, D. (2000). Real-time Noise Cancelling Based on Spectral Minimum Detection and Diffusive Gain Factors,. Proceedings of the 8th Australian International Conference on Speech Science & Technology, 256 – 261.,


Kim, H., Obermayer, K., Bode, M. and Ruwisch, D. (2000). A 1.6 KBPS Speech Codec Using Spectral Vector Quantization of Differential Features. Proceedings of the 8th Australian International Conference on Speech Science & Technology, 404 – 409.,


Kim, H., Obermayer, K. and Ruwisch, D. (2000). Real-Time Noise Cancelling with Spectral Diffusion. Proceedings of the 1st IEEE Electro/Information Technology Conference, 206 – EIT 536.,


Krepki, R., Pu, Y., Meng, H. and Obermayer, K. (1999). A New Algorithm for the Interrogation of 3D Holographic Particle Tracking Velocimetry Data Based on Deterministic Annealing and EM-Optimizazion. 3rd International Workshop on Particle Image Velocimetry. PIV \'99, Santa Barbara, CA, USA, (1 – 14).,


Kuzmanovski, A., Stellmacher, M. and Obermayer, K. (1998). A New Algorithm for the Evaluation of PTV Data Using Point Matching Distance Mesaures and Deterministic Annealing. Proc. Int. Symp. on Appl. of Laser Techniques to Fluid Mechanics, 10.4.1 – 10.4.6.,


Lund, J. and Obermayer, K. (2002). Visual Cortex: Anatomical Structure and Models of Function. The Handbook of Brain Theory and Neural Networks. MIT Press, 1202 – 1205.,


Machenschalk, B., Pieenbrock, C. and Obermayer, K. (1998). The Role of Competitive Cortical Interactions in the Development of Orientation Selectivity Maps. European J. Neurosc, 10(S10):pg 243. European Forum of Neuroscience ENA.,


Mahler, G. and Obermayer, K. (1987). Towars the Quantum Computer: Information Processing with Single Electrons. Computational Systems - Natural and Artificial. Springer, 154 – 165.,10.1007/978-3-642-73089-4_13


Martin, R. and Obermayer, K. (2009). Theoretical and Computational Neuroscience: Self-Organizing Maps. The Encyclopedia of Neuroscience. Academic Press, 561 – 570.,


Martinez, E., Adiloglu, K., Annies, R., Purwins, H. and Obermayer, K. (2007). Representation of Everyday Sounds for Classification of their Perceived Function. Proc. Audio Mostly Conference, 90 – 95.,


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.,


Mohr, J., Hess, A., Scholz, M. and Obermayer, K. (2002). Automatic Extraction of Anatomical and Functional Brain Data from Autoradiographic Image Stacks. Data analysis, physiological methods, statistics II, Soc. Neurosci. Abstr., 312.14.,


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