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Titlebook: Computational Intelligence in Intelligent Data Analysis; Christian Moewes,Andreas Nürnberger Conference proceedings 2013 Springer-Verlag B

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Feedback-Driven Design of Normalization Techniques for Biological Images Using Fuzzy Formulation of intensity information in a digital image is mostly distorted due to imperfect acquisition conditions resulting in the shading phenomenon. Additionally, the high contrast of gray values present in an image also imparts a bias to retrieved gray values. Consequently, image processing goals such as segm
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Strategien optimaler Repatriierungetworks had been rediscovered and triggered a massive new interest in neural networks. The approach of combining fuzzy systems with neural networks into neuro-fuzzy systems therefore was an obvious choice for making fuzzy systems learn. In this chapter we briefly recall some milestones on the evolution of neuro-fuzzy systems.
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Untersuchungsgebiet und Ethnographie,tional means have to be employed in the objective function in order to obtain actual degrees of membership. This paper surveys the most common fuzzification means and examines and compares their properties.
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