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Udo Seiffert: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Udo Seiffert
    Adaptive Implementation of Artificial Neural Networks Reflecting Changing Hardware Resources at Run-Time. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence and Applications, 2005, pp:733-737 [Conf]
  2. Udo Seiffert, Bernd Michaelis
    Three-dimensional Self-Organizing Maps for Classification of Image Properties. [Citation Graph (0, 0)][DBLP]
    ANNES, 1995, pp:310-313 [Conf]
  3. Andreas Herzog, G. Sommerkorn, Udo Seiffert, Bernd Michaelis, Katharina Braun, Werner Zuschratter
    Rekonstruktion und Klassifikation dendritischer Spines aus konfokalen Bilddaten. [Citation Graph (0, 0)][DBLP]
    Bildverarbeitung für die Medizin, 1996, pp:- [Conf]
  4. Thomas Villmann, Barbara Hammer, Udo Seiffert
    Perspectives of Self-adapted Self-organizing Clustering in Organic Computing. [Citation Graph (0, 0)][DBLP]
    BioADIT, 2006, pp:141-159 [Conf]
  5. Udo Seiffert
    Biologically Inspired Image Compression in Biomedical High-Throughput Screening. [Citation Graph (0, 0)][DBLP]
    BioADIT, 2004, pp:428-439 [Conf]
  6. Gerald Krell, R. Rebmann, Udo Seiffert, Bernd Michaelis
    Improving Still Image Coding by an SOM-Controlled Associative Memory. [Citation Graph (0, 0)][DBLP]
    CIARP, 2003, pp:571-579 [Conf]
  7. Alexander Ihlow, Udo Seiffert
    Automating Microscope Colour Image Analysis Using the Expectation Maximisation Algorithm. [Citation Graph (0, 0)][DBLP]
    DAGM-Symposium, 2004, pp:536-543 [Conf]
  8. R. Rebmann, Gerald Krell, Udo Seiffert, Bernd Michaelis
    Associative Correction Of Compression Artefacts With A Self-Organizing Map Classifying The Image Content. [Citation Graph (0, 0)][DBLP]
    DCC, 2003, pp:446- [Conf]
  9. Cornelia Brüß, Felix Bollenbeck, Frank-Michael Schleif, Winfriede Weschke, Thomas Villmann, Udo Seiffert
    Fuzzy image segmentation with Fuzzy Labelled Neural Gas. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:563-568 [Conf]
  10. Marc Strickert, Nese Sreenivasulu, Udo Seiffert
    Sanger-driven MDSLocalize - a comparative study for genomic data. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:265-270 [Conf]
  11. Marc Strickert, Nese Sreenivasulu, Winfriede Weschke, Udo Seiffert, Thomas Villmann
    Generalized Relevance LVQ with Correlation Measures for Biological Data. [Citation Graph (0, 0)][DBLP]
    ESANN, 2005, pp:331-338 [Conf]
  12. Udo Seiffert
    Multiple Layer Perceptron training using genetic algorithms. [Citation Graph (0, 0)][DBLP]
    ESANN, 2001, pp:159-164 [Conf]
  13. Udo Seiffert
    Artificial Neural Networks on Massively Parallel Computer Hardware. [Citation Graph (0, 0)][DBLP]
    ESANN, 2002, pp:319-330 [Conf]
  14. Udo Seiffert, Barbara Hammer, Samuel Kaski, Thomas Villmann
    Neural networks and machine learning in bioinformatics - theory and applications. [Citation Graph (0, 0)][DBLP]
    ESANN, 2006, pp:521-532 [Conf]
  15. Thomas Villmann, Udo Seiffert, Axel Wismüller
    Theory and applications of neural maps. [Citation Graph (0, 0)][DBLP]
    ESANN, 2004, pp:25-38 [Conf]
  16. Axel Wismüller, Udo Seiffert
    Digital Image Processing with Neural Networks. [Citation Graph (0, 0)][DBLP]
    ESANN, 2003, pp:493-502 [Conf]
  17. Alexander Ihlow, Udo Seiffert
    Haustoria Segmentation in Microscope Colour Images of Barley Cells. [Citation Graph (0, 0)][DBLP]
    Workshop Farbbildverarbeitung, 2004, pp:119-126 [Conf]
  18. Vaijayanti Joshi, Lakhmi C. Jain, Udo Seiffert, Kathleen Zyga, Richard Price, Friedrich Leisch
    Neural Techniques in Logo Recognition. [Citation Graph (0, 0)][DBLP]
    HIS, 2001, pp:25-32 [Conf]
  19. Marc Strickert, Stefan Teichmann, Nese Sreenivasulu, Udo Seiffert
    High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2005, pp:625-633 [Conf]
  20. R. Rebmann, Bernd Michaelis, Gerald Krell, Udo Seiffert, F. Püschel
    Improving Image Processing Systems by Artificial Neural Networks. [Citation Graph (0, 0)][DBLP]
    Reading and Learning, 2004, pp:37-64 [Conf]
  21. Udo Seiffert, Bernd Michaelis
    Indirect Unsuperivised Training of Backpropagation Nets. [Citation Graph (0, 0)][DBLP]
    SIP, 1999, pp:328-332 [Conf]
  22. Ralf Tautenhahn, Alexander Ihlow, Udo Seiffert
    Adaptive Feature Selection for Classification of Microscope Images. [Citation Graph (0, 0)][DBLP]
    WILF, 2005, pp:215-222 [Conf]
  23. Marc Strickert, Nese Sreenivasulu, Silke Peterek, Winfriede Weschke, Hans-Peter Mock, Udo Seiffert
    Unsupervised Feature Selection for Biomarker Identification in Chromatography and Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    ANNPR, 2006, pp:274-285 [Conf]
  24. Thomas Villmann, Udo Seiffert, Frank-Michael Schleif, Cornelia Brüß, Tina Geweniger, Barbara Hammer
    Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes. [Citation Graph (0, 0)][DBLP]
    ANNPR, 2006, pp:46-56 [Conf]
  25. Udo Seiffert, Bernd Michaelis
    Growing 3D-SOMs with 2D-Input Layer as a Classification Tool in a Motion Detection System. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 1997, v:8, n:1, pp:81-89 [Journal]
  26. Udo Seiffert
    Artificial neural networks on massively parallel computer hardware. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2004, v:57, n:, pp:135-150 [Journal]
  27. Marc Strickert, Udo Seiffert, Nese Sreenivasulu, Winfriede Weschke, Thomas Villmann, Barbara Hammer
    Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:69, n:7-9, pp:651-659 [Journal]
  28. Udo Seiffert, Bernd Michaelis
    Estimating Motion Parameters with Three-Dimensional Self-Organizing Maps. [Citation Graph (0, 0)][DBLP]
    Inf. Sci., 1997, v:101, n:3-4, pp:187-201 [Journal]

  29. Towards Automatic Segmentation of Serial High-Resolution Images. [Citation Graph (, )][DBLP]

  30. Correlation-based Data Representation. [Citation Graph (, )][DBLP]

  31. Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data. [Citation Graph (, )][DBLP]

  32. Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS. [Citation Graph (, )][DBLP]

  33. Machine learning approches and pattern recognition for spectral data. [Citation Graph (, )][DBLP]

  34. Intuitive Clustering of Biological Data. [Citation Graph (, )][DBLP]

  35. Training of Large-Scale Feed-Forward Neural Networks. [Citation Graph (, )][DBLP]

  36. Fast registration-based automatic segmentation of serial section images for high-resolution 3-D plant seed modeling. [Citation Graph (, )][DBLP]

  37. 4D Warping for Analysing Morphological Changes in Seed Development of Barley Grains. [Citation Graph (, )][DBLP]

  38. Multimodal Registration of NMR-volumes and Histological Cross-sections of Barley Grains on the Cell Broadband Engine Processor. [Citation Graph (, )][DBLP]

  39. From Individual Intensity Voxel Data to Inter-individual Probabilistic Atlases of Biological Objects by an Interleaved Registration-segmentation Approach. [Citation Graph (, )][DBLP]

  40. Remote Rendering of Large Biological Datasets. [Citation Graph (, )][DBLP]

  41. Adaptive three-dimensional self-organizing map with a two-dimensional input layer. [Citation Graph (, )][DBLP]

  42. Three-Dimensional Multimodality Modelling by Integration of High-Resolution Interindividual Atlases and Functional MALDI-IMS Data. [Citation Graph (, )][DBLP]

  43. Correlation-maximizing surrogate gene space for visual mining of gene expression patterns in developing barley endosperm tissue. [Citation Graph (, )][DBLP]

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