Hon.-Prof. Dr.-Ing. Udo Seiffert

Hon.-Prof. Dr.-Ing. Udo Seiffert

Institut für Informations- und Kommunikationstechnik (IIKT)
Department of Neuro-Information Technology
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Ausgewählte Publikationen

  • Seiffert, U.: ANNIE - Artificial Neural Network-based Image Encoder. Neurocomputing, Vol. 125, pp. 229-235, 2014.

  • Knauer, U.; Seiffert, U.: Cascaded Reduction and Growing of Result Sets for Combining Object Detectors. Proc. of the 11. International Conference on Multiple Classifier Systems MCS 2013, Nanjing, China, pp. 121-133, 2013.

  • Villmann, T.; Kästner, M.; Backhaus, A.; Seiffert, U.: Processing Hyperspectral Data in Machine Learning. Proc. of the 21. European Symposium on Artificial Neural Networks ESANN 2013, Bruges, Belgium, pp. 1-10, D-Side Publications, Evere, Belgium, 2013.

  • Kirsten, S.; Navarro-Quezada, A.; Penselin, D.; Wenzel, C.; Matern, A.; Leitner, A.; Baum, T.; Seiffert, U.; Knogge, W.: Necrosis-inducing Proteins of Rhynchosporium Commune, Effectors in Quantitative Disease Resistance. Molecular Plant-Microbe Interactions, Vol. 25, pp. 1314-1325, 2012.

  • Backhaus, A.; Lachmair, J.; Rückert, U.; Seiffert, U.: Hardware Accelerated Real Time Classification of Hyperspectral Imaging Data for Coffee Sorting. Proc. of the 20. European Symposium on Artificial Neural Networks ESANN 2012, Bruges, Belgium, pp. 627-632, D-Side Publications, Evere, Belgium, 2012.

  • Backhaus, A.; Ashok, P.C.; Praveen, B.B.; Dholakia, K.; Seiffert, U.: Classifying Scotch Whisky from Near-infrared Raman Spectra with Radial Basis Function Network with Relevance Learning. Proc. of the 20. European Symposium on Artificial Neural Networks ESANN 2012, Bruges, Belgium, pp. 411-416, D-Side Publications, Evere, Belgium, 2012.

  • Kästner, M.; Backhaus, A.; Geweniger, T.; Haase, S.; Seiffert, U.; Villmann, T.: Relevance Learning in Unsupervised Vector Quantization Based on Divergences. Proc. of the 8. International Workshop on Self-Organizing Maps WSOM 2011, Espoo, Finland, pp. 90-100, 2011.

  • Seiffert, U.; Schleif, F.M.; Zühlke, D.: Recent Trends in Computational Intelligence in Life Sciences. Proc. of the 19. European Symposium on Artificial Neural Networks ESANN 2011, Bruges, Belgium, pp. 77-86, D-Side Publications, Evere, Belgium, 2011.

  • Baum, T.; Navarro-Quezada, A.; Knogge, W.; Douchkov, D.; Schweizer, P.; Seiffert, U.: HyphArea - Automated analysis of spatiotemporal fungal patterns. Journal of Plant Physiology, Vol. 168, pp. 72-78, 2011.

  • Bollenbeck, F.; Seiffert, U.: Joint Registration and Segmentation of Histological Volume Data by Diffusion-based Label Adaptation. Proc. of the IEEE International Conference on Pattern Recognition ICPR 2010, Istanbul, Turkey, pp. 2440-2443, IEEE Press, Piscataway, USA, 2010.

  • Backhaus, A.; Kuwabara, A; Fleming, A.; Seiffert, U.: Validation of Unsupervised Clustering Methods for Leaf Phenotype Screening. Proc. of the 18. European Symposium on Artificial Neural Networks ESANN 2010, Bruges, Belgium, pp. 511-516, D-Side Publications, Evere, Belgium, 2010.

  • Bollenbeck, F.; Seiffert, U.: Computational Intelligence in Biomedical Image Processing. In Abraham, A. et. al (Eds.): Foundations of Computational Intelligence - Vol. 5, pp. 197-222, Springer, Berlin, 2009.

  • Bollenbeck, F.; Kaspar, S.; Mock, H.-P.; Weier, D.; Seiffert, U.: Three-dimensional Multimodality Modelling by Integration of High-Resolution Interindividual Atlases and Functional MALDI-IMS Data. In Rajasekaran, S. (Ed.): Bioinformatics and Computational Biology. LNBI 5462, pp. 126-139, Springer, Berlin, 2009.

  • Ihlow, A.; Schweizer, P.; Seiffert, U.: A High-throughput Screening System for Barley/Powdery Mildew Interactions Based on Automated Analysis of Light Micrographs. BMC Plant Biology, Vol. 8, No. 6, 2008.

  • Seiffert, U.; Bollenbeck, F.: Fuzzy Image Segmentation by Potential Fields. Proc. of the IEEE World Conference on Computational Intelligence WCCI 2008 / International Conference on Fuzzy Systems FS 2008, Hong Kong, pp. 1118-1123, IEEE Press, 2008.

  • Villmann, T.; Merenyi, E.; Seiffert, U.: Machine Learning Approaches and Pattern Recognition for Spectral Data. Proc. of the 16. European Symposium on Artificial Neural Networks ESANN 2008, Bruges, Belgium, pp. 433-444, D-Side Publications, Evere, Belgium, 2008.

  • Villmann, T.; Hammer, B.; Seiffert, U.:  Perspectives of Self-Adapted Self-Organizing Clustering in Organic Computing. In Ijspeert, A.J. et al. (Eds.): Biologically Inspired Approaches to Advanced Information Technology. LNCS 3853. pp. 141-159, Springer, Berlin, 2006.

  • Seiffert, U.: Training of Large-Scale Feed-Forward Neural Networks. Proc. of the IEEE World Conference on Computational Intelligence WCCI 2006 / International Joint Conference on Neural Networks IJCNN 2006, Vancouver, Canada, pp. 10780-10785, IEEE Press, 2006.

  • Seiffert, U.; Hammer, B.; Kaski, S.; Villmann, T.: Neural Networks and Machine Learning in Bioinformatics. Proc. of the 14. European Symposium on Artificial Neural Networks ESANN 2006, Bruges, Belgium, pp. 521-532, D-Side Publications, Evere, Belgium, 2006.

  • Seiffert, U.; Schweizer, P.: A Pattern Recognition Tool for Quantitative Analysis of In Planta Hyphal Growth of Powdery Mildew Fungi. Molecular Plant Microbe Interactions (MPMI), Vol. 19, No. 9, pp. 906-912, 2005.

  • Seiffert, U.: Content Adaptive Compression of Images Using Neural Maps. Proc. of the International Workshop on Self-Organizing Maps WSOM 2005, Paris, France, pp. 227-234, 2005.

  • Seiffert, U.; Jain, L.C., Schweizer, P. (Eds.): Bioinformatics using Computational Intelligence Paradigms. Springer, Heidelberg, 2005.

  • Seiffert, U.: Artificial Neural Networks on Massively Parallel Computer Hardware. Neurocomputing, Vol. 57, pp. 135-150, 2004.

  • Seiffert, U.: Biologically Inspired Image Compression in Biomedical High-Throughput Screening. In Ijspeert, A.J. et al. (Eds.): Biologically Inspired Approaches to Advanced Information Technology. LNCS 3141. pp. 428-440, Springer, Heidelberg, 2004.

  • Seiffert, U.; Jain, L.C. (Eds.): Self-Organizing Maps. Recent Advances and Applications. Springer, Heidelberg, 2001.

  • Seiffert, U.; Michaelis, B.: Growing Multi-Dimensional Self-Organizing Maps. International Journal of Knowledge-Based Intelligent Engineering Systems, Vol. 2, No. 1, pp. 42-48, 1998.

Die komplette Publikationsliste bzw. Sonderdrucke sind auf Anfrage erhältlich.

  • Fraunhofer-Institut für Fabrikbetrieb und -automatisierung IFF
  • Soft Computing, insb. künstliche neuronale Netze, genetische/evolutionäre Algorithmen
  • Bildverarbeitung, Mustererkennung, Data Mining
  • Räumlich-zeitliche Modellierung biologischer Entwicklungsvorgänge
  • Paralleles und verteiltes Rechnen, Spezialhardware für neuronale Netze
  • Selbstadaptierende Systeme/Hardware, Organic Computing

Work History

1993 Diplomingenieur für Automatisierungstechnik (Universität Magdeburg)
1998 Promotion zum Dr.-Ing. (Universität Magdeburg)
2000 DAAD Auslandsstipendium (University of South Australia, Adelaide)
2002 Arbeitsgruppenleiter Mustererkennung (Leibniz-Institut IPK, Gatersleben)
2008 Honorarprofessur Neuronale Systeme (Universität Magdeburg)
2008 Leiter Kompetenzfeld Biosystems Engineering (Fraunhofer-Institut IFF, Magdeburg)

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