M. Kreutz

发表

Using fitness distributions to improve the evolution of learning structures

C. Igel, M. Kreutz, 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

Diagnostic and neural analysis of skin cancer (DANAOS). A multicentre study for collection and computer‐aided analysis of data from pigmented skin lesions using digital dermoscopy

P Altmeyer, L Andreassi, R. Perotti, 2003, The British journal of dermatology.

Regularization and Model Selection in the Context of Density Estimation

Anja M. Reimetz, W. Seelen, C. Weihs, 1999 .

Operator adaptation in evolutionary computation and its application to structure optimization of neural networks

Christian Igel, Martin Kreutz, C. Igel, 2003, Neurocomputing.

Solving Extended Hybrid-Flow-Shop Problems Using Active Schedule Generation and Genetic Algorithms

M. Kreutz, S. Gehlen, D. Hanke, 2000, PPSN.

Scale-invariant image recognition based on higher-order autocorrelation features

Herbert Janssen, Martin Kreutz, Bernd Völpel, 1996, Pattern Recognit..

Automated Diagnosis of Skin Cancer: Using Digital Image Processing and Mixture-of-Experts

Klaus Hoffmann, Stefan Gehlen, Martin Kreutz, 2001, Bildverarbeitung für die Medizin.

Analysis of Possible Genome-Dependence of Mutation Rates in Genetic Algorithms

Bernhard Sendhoff, Martin Kreutz, B. Sendhoff, 1996, Evolutionary Computing, AISB Workshop.

A Condition for the Genotype-Phenotype Mapping: Causality

Bernhard Sendhoff, Werner von Seelen, Martin Kreutz, 1997, ICGA.

Evolutionary Optimization of the Structure of Neural Networks by a Recursive Mapping as Encoding

B. Sendhoff, M. Kreutz, B. Sendhoff, 1997, ICANNGA.