Wyniki wyszukiwania - BazTech

1

On the order equivalence relation of binary association measures

Paradowski M.

International Journal of Applied Mathematics and Computer Science

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2015

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Vol. 25, no. 3

645--657

EN

Over a century of research has resulted in a set of more than a hundred binary association measures. Many of them share similar properties. An overview of binary association measures is presented, focused on their order equivalences. Association measures are grouped according to their relations. Transformations between these measures are shown, both formally and visually. A generalization coefficient is proposed, based on joint probability and marginal probabilities. Combining association measures is one of recent trends in computer science. Measures are combined in linear and nonlinear discrimination models, automated feature selection or construction. Knowledge about their relations is particularly important to avoid problems of meaningless results, zeroed generalized variances, the curse of dimensionality, or simply to save time.

2

Bag of Words : Quality Issues of Near-Duplicate Image Retrieval

Paradowski M., Durak M., Broda B.

Machine Graphics and Vision

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2014

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Vol. 23, No. 1/2

83--96

EN

This paper addresses the problem of large scale near-duplicate image retrieval. Issues related to visual words dictionary generation are discussed. A new spatial verification routine is proposed. It incorporates neighborhood consistency, term weighting and it is integrated into the Bhattacharyya coefficient. The proposed approach reaches almost 10% higher retrieval quality, comparing to other recently reported state-of-the-art methods.

3

BHP w warunkach pracy umysłowej

Knapik A., Paradowski M.

Zeszyty Naukowe Wyższej Szkoły Zarządzania Ochroną Pracy w Katowicach

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2013

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Nr 1(9)

135--144

PL

Niniejszy artykuł porusza istotne zagadnienia z zakresu bezpiecznych i higienicznych warunków pracy. Na wstępie wskazuje on na znaczenie BHP w stosunkach pracowniczych oraz odnosi się do genezy zagadnienia. W swej zasadniczej części koncentruje on uwagę na ustaleniu rozumienia znaczenia terminu BHP. W części końcowej z kolei odnosi się do bezpieczeństwa i higieny pracy w warunkach pracy umysłowej podkreślając na konsekwencje zdrowotne.

EN

This article tackles valid issues connected with safe and health-friendly work environment. In its introductory part it shows the significance of work health and safety in company industrial relations (IR) and refers back to the origins of this issue. In its main part the article focuses on establishing the meaning of the issue of work health and safety whereas in its final part it draws on work health and safety in mental work environment emphasising its health-related effects.

4

Improved Resulted Word Counts Optimizer for Automatic Image Annotation Problem

Paradowski M., Kwasnicka H.

Fundamenta Informaticae

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2009

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Vol. 96, nr 4

435-463

EN

Automatic Image Annotation is an important research topic in pattern recognition area. There are many different approaches to Automatic Image Annotation. In many of these approaches a key problem is determining correct word distributions in the generated annotations. Incorrect word distributions (word frequencies) results in large reduction of annotation quality. The paper presents a generic approach to find correct word frequencies. The approach may be used with many automatic image annotators, based on various machine learning paradigms. Proposed method is an improved version of our already presented method, called Greedy Resulted Word Counts Optimization. The key differences and novelties in the paper are: the concept of border support values and a method of optimal step selection in the optimization routine. Optimal step selection allows to reduce the number of computations during the optimization procedure, comparing to old Greedy Resulted Word Counts Optimization method.

5

Fast image auto-annotation with discretized feature distance measures

Kwasnicka H., Paradowski M.

Machine Graphics and Vision

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2006

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Vol. 15, No. 2

123-140

EN

A new model for the image auto-annotation task is presented. The model can be classified as a fast image auto-annotation one. The main idea behind the model is to avoid various problems with feature space clustering. Both the image segmentation and the auto-annotation process do not, use any clustering algorithms. The method presented here simulates continuous feature space analysis with very dense discretization. The paper presents the new approach and discusses the results achieved with it.