Cubaleska, B., Schöner, G. & Giese, M. A. (1997). Separation of feed-forward and recurrent parts of neural representations based on population techniques. In Elsner N, Wässle H (eds): Göttingen Neurobiology Report 1997. Thieme Verlag, Stuttgart, 1017.
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Our Research Areas
Schöner, G., Hock, H. S. & Giese, M. A. (1997). Neural field dynamics for the perceptual organization of motion. Investigative Ophtalmology and Visual Sciences, 38, p.936.
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Giese, M. A. (1998). Effiziente Methode zur Implementierung dynamischer neuronaler Felder. Patent No. 198 44 364.1. Deutsches Patentamt, München.
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Massberg, W., Weigt, D., Steinhage, A., Schöner, G. & Giese, M. A. (1998). Selbstorganisierende Fertigungssteuerung: Selbstorganisierendes Modell der Fertigungssteuerung auf der Basis neuronaler Dynamik. WT Werkstatt Technik, 7/8-98, 329-332.
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Giese, M. A. (1998). Dynamic neural field model links neural and computational theories of motion perception. Workshop Dynamische Perzeption. Infix Verlag, St. Augustin, Germany.
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Giese, M. A. (1998). A Dynamic Neural Field Model for the Perception of Apparent Motion. Phd Thesis.
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Cubaleska, B., Akhavan, A. C., Jancke, D., Dinse, H. R., Schöner, G. & Giese, M. A. (1998). Separation of feed-forward and recurrent parts of cortical dynamics in cat area 17. In Elsner N, Wehner R (eds): Göttingen Neurobiology Report 1998. Thieme Verlag, Stuttgart, 469.
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Giese, M. A. (1999). Evidence for Multi-functional Interactions in Early Visual Motion Processing,. Trends in Neurosciences, 22, 287-290.
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Giese, M. A. (1999). Quick work but variable quality. Nature, 401(13).
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Jancke, D., Erlhagen, W., Dinse, H. R., Akhavan, A. C., Steinhage, A., Schöner, G. et al. (1999). Population representation of retinal position in cat primary visual cortex: interaction and dynamics. Journal of Neuroscience, 19(20), 9016-9028.
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Poggio, T. A. & Giese, M. A. (1999). Synthesis and Recognition of Biological Motion Patterns Based on Linear Superposition of Prototypical Motion Sequences. In: Proceedings of the IEEE Workshop on Multi-View Modeling and Analysis of Visual Scene, Fort Collins, CO, June 21-23, 1999., 73-80.
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Dinse, H. R., Jancke, D., Akhavan, A. C., Kalt, T., Schöner, G. & Giese, M. A. (1999). Dynamic population representations of the visual and somatosensory cortex. Proceedings of the International Conference on Neural Information Processing 96. Springer, NY, 1285-1290.
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Poggio, T. A. & Giese, M. A. (1999). Recognition and synthesis of biological motion patterns by linear combination of prototypical motion patterns. In Elsner N, Eysel U (eds): Göttingen Neurobiology Report 1999. Thieme Verlag, Stuttgart, 501.
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Endres, D. & Riegler, P. (1999). Learning Dynamics on Different Timescales. Journal of Physics A: Mathematical and General, 32(49), 8655-8663.
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Giese, M. A. & Poggio, T. A. (2000). Quantification and Classification of Locomotion Patterns by Spatio-temporal Morphable Models. In: Third IEEE Workshop on Visual Surveillance, Dublin, Ireland, July 1, 2000.
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Giese, M. A. & Poggio, T. A. (2000). Morphable models for the analysis and synthesis of complex motion patterns. International Journal of Computer Vision, 38(1), 59-73.
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Giese, M. A. (2000). Neural field model for the recognition of biological motion. Second International ICSC Symposium on Neural Computation NC 2000, May 23-26, Berlin, Germany.
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Giese, M. A. (2000). Neural Model for the Recognition of Biological Motion. In: Dynamische Perzeption 2, G. Baratoff and H. Neumann (eds.), 105-110.
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Giese, M. A. (2000). Learning-based neural model for the recognition of biological motion. Conference of the Federation of European Neuroscience Research..
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Yu, A. J., Poggio, T. A. & Giese, M. A. (2000). Neural mechanisms for the realization of maximum operations. Conference of the Federation of European Neuroscience Research, Brighton, June, 2000..
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Yu, A. J., Poggio, T. A. & Giese, M. A. (2000). Neural circuits for the realization of maximum operation. Society of Neuroscience Abstracts, 26, 1202.
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Lappe, M. & Giese, M. A. (2000). Categorization of biological movement patterns. Investigative Ophtalmology and Visual Sciences, 41..
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Giese, M. A. (2000). Learning-based neural model for the recognition of biological motion patterns. Investigative Ophtalmology and Visual Sciences, 41.
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Moukovski, A., Gorinevski, D. M., Giese, M. A. & von Seelen, W. (2001). Formation of pinheels of preferred orientation by learning sparse neural representations of natural images. Neurocomputing 44-46(C):549-553. (reprinted in "Computational Neuroscience: Trends in Research" 2002, 1st ed., ISBN13:9780444511348, Elsevier Science {&} Technology.).
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Xie, X. & Giese, M. A. (2001). Generating velocity tuning by asymmetric recurrent connections. In: T. G. Dietterich and S. Becker and Z. Ghahramani (eds): Advances in Neural Information Processing Systems, 14.
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