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Dr. Julia Neumann

Inhaltsbereich / Content

Dr. Julia Neumann

New affiliation

Dr. Julia Neumann
Tableau
An der Welle 4
60322 Frankfurt am Main
Deutschland

http://www.tableau.com/de-de

Publications

  • J. Neumann (December 2004).
    Adaptive Conjoint Wavelet-Support Vector Classifiers.
    University of Mannheim (PhD Thesis)
    [BibTex]

  • G. Steidl and S. Didas and J. Neumann (2006).
    Splines in higher order TV regularization.
    International Journal of Computer Vision. 70, 241--255.
    [pdf] [BibTex]

  • J. Neumann and C. Schnörr and G. Steidl (2005).
    Combined SVM-based feature selection and classification.
    Machine Learning. 61, 129--150.
    [pdf] [BibTex]

  • J. Neumann and C. Schnörr and G. Steidl Nov (2005).
    Efficient Wavelet Adaption for Hybrid Wavelet-Large Margin Classifiers.
    Pattern Recognition. 38, (11), 1815--1830.
    [pdf] [BibTex]

  • J. Neumann and G. Steidl (2005).
    Dual-tree complex wavelet transform in the frequency domain and an application to signal classification.
    International Journal of Wavelets, Multiresolution and Information Processing. 3, (1), 43--66.
    [pdf] [BibTex]

  • G. Steidl and S. Didas and J. Neumann (2005).
    Relations between higher order TV regularization and support vector regression.
    Scale-Space and PDE Methods in Computer Vision. R. Kimmel and N. Sochen and J. Weickert (eds.) LNCS 3459, 515--527.
    [pdf] [BibTex]
  • J. Neumann and C. Schnörr and Steidl (2004).
    SVM-based feature selection by direct objective minimisation.
    Pattern Recognition. C. E. Rasmussen and H. H. Bülthoff, M. A. Giese and B. Schölkopf (eds.) LNCS 3175, 212--219.
    [pdf] [BibTex]
  • J. Neumann and C. Schnörr and G. Steidl (2003).
    Feasible adaptation criteria for hybrid wavelet - large margin classifiers.
    N. Petkov and M. A. Westenberg (eds.) Computer Analysis of Images and Patterns. Springer: Berlin 588--599.
    [BibTex]