Wyniki wyszukiwania - Biblioteka Nauki

1

Klasyfikatory z gradacją błędów wykorzystujące sumę rang

100%

Stawska Z. , Jóźwik A.

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2005

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tom T. 9, z. 3

563-569

PL

W artykule została zaproponowana modyfikacja schematu podejmowania decyzji opartego na regule k najbliższych sąsiadów, polegająca na wprowadzeniu gradacji błędu. Stosowane do tej pory metody rozpoznawania obrazów pozwalają na ocenę jakości klasyfikacji jako funkcji prawdopodobieństwa mylnej decyzji. Prawdopodobieństwo to szacowane jest eksperymentalnie jako średni błąd klasyfikacji obiektów o znanej przynależności. Wprowadzenie gradacji błędów umożliwia oszacowanie prawdopodobieństwa mylnej decyzji w zależności od cech klasyfikowanego obiektu.

EN

A modification of the k nearest neighbor rule, which enables the classification confidence, is proposed. The quality of the standard classifiers is measured by the probability of misclassification estimated experimentally by a use of objects with known elass membership. The error rate is computed as the percentage of misclassified objects. An error rate gradation enables the evaluation of the misclassification probability as a function of the object feature values.

2

Support vector machine in gender recognition

100%

Stawska Z. , Milczarski P.

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tom Vol. 6, No. 4

318--329

EN

In the paper, Support Vector Machine (SVM) methods are discussed. The SVM algorithm is a very strong classification tool. Its capability in gender recognition in comparison with the other methods is presented here. Different sets of face features derived from the frontal facial image such as eye corners, nostrils, mouth corners etc. are taken into account. The efficiency of different sets of facial features in gender recognition using SVM method is examined.

3

Complex colour detection methods used in skin detection systems

100%

Milczarski P. , Stawska Z.

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2014

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tom Vol. 3, No. 1

40--52

EN

In this paper we present high computational complexity algorithms for detecting skin and non-skin colour. Because of their complexity they are not suitable for nowadays mobile devices but can be used in systems working on more demanding machines. The selection and implementation of algorithms gives accuracy about 80-90%.

4

Gender recogniotion methods useful in mobile authentication applications

100%

Stawska Z. , Milczarski P.

Information Systems in Management

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2016

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tom Vol. 5, No. 2

248--259

EN

Soft biometrics methods that involve gender, age and ethnicity are still developed. Face recognition methods often rely on gender recognition. The same applies to the methods reconstructing the faces or building 2D or 3D models of the faces. In the paper, we conduct study on different set of gender recognition methods and their mobile applications. We show the advantages and disadvantages of that methods and future challenges to the researches. In the previous papers, we examined a range variety of skin detection methods that help to spot the face in the images or video stream. On acquiring faces, we focus on gender recognition that will allow us to create pattern to build 2D and 3D automatic faces models from the images. That will result also in face recognition and authentication, also.

5

Klasyfikatory z oceną wiarygodności decyzji i ich zastosowanie do wyboru strategii leczenia

61%

Stawska Z. , Jóźwik A. , Grabowski M. , Filipiak K. , Rudowski R. , Opolski G.

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2004

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tom T. 8, z. 3

331-338

PL

W artykule została zaproponowana modyfikacja schematu podejmowania decyzji opartego na regule k najbliższych sąsiadów, polegająca na wprowadzeniu gradacji błędu. Stosowane do tej pory metody rozpoznawania obrazów pozwalają na ocenę jakości klasyfikacji jako funkcji prawdopodobieństwa mylnej decyzji. Prawdopodobieństwo to szacowane jest eksperymentalnie jako średni błąd klasyfikacji obiektów o znanej przynależności. Wprowadzenie gradacji błędów umożliwia oszacowanie prawdopodobieństwa mylnej decyzji w zależności od cech klasyfikowanego obiektu. Przedstawione podejście zostało zastosowane do analizy rzeczywistych danych dotyczących problemu rozpoznawania pacjentów z ostrym zespołem wieńcowym.

EN

A modification of the k nearest neighbor rule, which enables the classification confidence, is proposed. The quality of the standard classifiers is measured by the probability of misclassification estimated experimentally by a use of objects with known class membership. The error rate is computed as the percentage of misclassified objects. An error rate gradation enables the evaluation of the misclassification probability as a function of the object feature values. The presented approach was applied to an analysis of a real data related to the patients with acute coronary syndromes.

6

Distance based classifiers and their use to analysis of data concerned acute coronary syndromes

61%

Jóźwik A. , Stawska Z. , Grabowski M. , Filipiak K. , Rudowski R. , Opolski G.

Image Processing & Communications

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2003

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tom Vol. 9, no 3-4

45-52

EN

The paper presents effectiveness of classifiers based on distance function in application to real problem concerned acute coronary syndromes. The types of decision rules: the standard k-NN rule; its fuzzy version and the multistage decision rule that uses the class overlap idea are considered. In the case of the fuzzy k-NN rule the fuzzyness is applied only for decreasing a misclassification rate. The multistage classifier is taken into account because of its very desired property, which consist in possibility of determination whether a case being classified is difficult or easy for recognition. The more difficult is the case to be classified the more stages are required. This property enables an error rate gradation. In each stage the proposed classifier can make up one of the three following decisions: indicate a class number, reply :"I do not know" or qualifythe object to the next stage. A number of stages depend on the classified object. The analyzed data concern to the two-class decision problem that consist in prediction whether the patient will survive the period of one month or not.