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Featureless pattern classification

Robert P. W. Duin, Dick de Ridder, David M. J. Tax (1998)

Kybernetika

In this paper the possibilities are discussed for training statistical pattern recognizers based on a distance representation of the objects instead of a feature representation. Distances or similarities are used between the unknown objects to be classified with a selected subset of the training objects (the support objects). These distances are combined into linear or nonlinear classifiers. In this approach the feature definition problem is replaced by finding good similarity measures. The proposal...

Finite volume schemes for the generalized subjective surface equation in image segmentation

Karol Mikula, Mariana Remešíková (2009)

Kybernetika

In this paper, we describe an efficient method for 3D image segmentation. The method uses a PDE model – the so called generalized subjective surface equation which is an equation of advection-diffusion type. The main goal is to develop an efficient and stable numerical method for solving this problem. The numerical solution is based on semi-implicit time discretization and flux-based level set finite volume space discretization. The space discretization is discussed in details and we introduce three...

Fuzzy clustering: Insights and new approach.

Frank Klawonn (2004)

Mathware and Soft Computing

Fuzzy clustering extends crisp clustering in the sense that objects can belong to various clusters with different membership degrees at the same time, whereas crisp or deterministic clustering assigns each object to a unique cluster. The standard approach to fuzzy clustering introduces the so-called fuzzifier which controls how much clusters may overlap. In this paper we illustrate, how this fuzzifier can help to reduce the number of undesired local minima of the objective function that is associated...

Fuzzy max-min classifiers decide locally on the basis of two attributes.

Birka von Schmidt, Frank Klawonn (1999)

Mathware and Soft Computing

Fuzzy classification systems differ from fuzzy controllers in the form of their outputs. For classification problems a decision between a finite number of discrete classes has to be made, whereas in fuzzy control the output domain is usually continuous, i.e. a real interval. In this paper we consider fuzzy classification systems using the max-min inference scheme and classifying an unknown datum on the basis of maximum matching, i.e. assigning it to the class appearing in the consequent of the rule...

Fuzzy sets in pattern recognition, image analysis and automatic speech recognition

Dwijesh Dutta Majumder (1985)

Aplikace matematiky

Fuzzy set theory, a recent generalization of classical set theory, has attracted the attention of researchers working in various areas including pattern recognition, which has had a seminal influence in the development of this new theory. This paper attempts to discuss some of the methodologies that have been suggested for pattern recognition, and techniques for image processing and speech recognition.

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