Applications

Seidel, R., Jahn, N., Seo, S., Goerttler, T. and Obermayer, K. (2022). NAPC: A Neural Algorithm for Automated Passenger Counting in Public Transport on a Privacy-Friendly Dataset. IEEE Open Journal of Intelligent Transportation Systems, 3, 33-44.

Trowitzsch I., Schymura C., Kolossa D. and K., O. (2019). Joining Sound Event Detection and Localization Through Spatial Segregation. IEEE Trans. Audio Speech Language Proc.

Trowitzsch, I., Mohr, J., Kashef, Y. and Obermayer, K. (2017). Robust Detection of Environmental Sounds in Binaural Auditory Scenes. IEEE Transactions on Audio Speech and Language Processing, 25, 1344-1356.

Trowitzsch, I., Taghia, J., Kashef, Y. and Obermayer, K. (2016). NIGENS Anechoic Ear Signals. Zenodo.,10.5281/zenodo.168042

Mohr, J., Park, J.-H. and Obermayer, K. (2014). A computer vision system for rapid search inspired by surface-based attention mechanisms from human perception. Neural Networks, 60, 182 - 193.

Schmidt, S., Scholz, M., Obermayer, K. and Brandt, S. A. (2013). Patterned Brain Stimulation, What a Framework with Rhythmic and Noisy Components Might Tell Us about Recovery Maximization. Frontiers in human neuroscience, 7

Adiloglu, K., Annies, R., Wahlen, E., Purwins, H. and Obermayer, K. (2012). A Graphical Representation and Dissimilarity Measure for Basic Everyday Sound Events. IEEE Transactions on Audio, Speech, and Language Processing, 1542 - 1552.

Neubauer, N. and Obermayer, K. (2011). Tripartite community structure in social bookmarking data. New Review of Hypermedia and Multimedia, 17, 267-294.

Mohr, J., Jain, B., Sutter, A., Laak, A., Steger-Hartmann, T., Heinrich, H. and Obermayer, K. (2010). A Maximum Common Subgraph Kernel Method for Predicting the Chromosome Aberration Test. Journal of Chemical Information and Modelling, 50, 1821–1838.

Natora, M., Franke, F., Broda, S. and Obermayer, K. (2010). Optimal Steering Vector Adaptation for Linear Filters Leading to Robust Beamforming. Proceedings of International Symposium on Communications, Control and Signal Processing. IEEE, 1 – 6.,10.1109/ISCCSP.2010.5463496

Neubauer, N. and Obermayer, K. (2010). Community Detection in Tagging-Induced Hypergraphs. Workshop on Information in Networks, 24.- 25. September 2010, New York University, NY, USA, 1-5.,

Pannicke, D., Hahne, M., Neubauer, N., Ochab, B., Lieb, R., Meister, M., Obermayer, K., Rammert, W. and Zarnekow, R. (2010). Akzeptanzfähigkeit von Tagging-Systemen in benutzergenerierten virtuellen Welten. Multikonferenz Wirtschaftsinformatik 2010. Universitätsverlag Göttingen, 1191 – 1201.,

Neubauer, N. and Obermayer, K. (2009). Hyperincident Connected Components in Tagging Networks. ACM SIGIWEB Newsletter, 229 – 238.

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., 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

Murfi, H. and Obermayer, K. (2009). A Two-Level Learning Hierarchy of Concept Based Keyword Extraction for Tag Recommendations. Proceedings ECML PKDD Discovery Challenge, 201 – 214.,

Natora, M., Franke, F. and Obermayer, K. (2009). Optimal Convolutive Filters for Real-Time Detection and Arrival Time Estimation of Transient Signals. Proceedings of World Academy of Science, Engineering and Technology. WASET, 235 – 240.,

Neubauer, N., Wetzker, R. and Obermayer, K. (2009). Tag Spam Creates Large Non-Giant Connected Components. AIRWeb '09 Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web. Association for Computing Machinery, 49 – 52.,10.1145/1531914.1531925

Mohr, J., Jain, B. and Obermayer, K. (2008). Molecule Kernels: A Descriptor- and Alignment-Free QSAR Approach. Journal of Chemical Information and Modeling, 48, 1868 – 1881.

Mohr, J., Seo, S. and Obermayer, K. (2008). Automated Microarray Classification Based on P-SVM Gene Selection. Proceedings of the ICMLA '08: The Seventh International Conference on Machine Learning and Applications. IEEE, 503 – 507.,10.1109/ICMLA.2008.75