Wyniki wyszukiwania - BazTech

1

Network Device Workload Prediction: A Data Mining Challenge at Knowledge Pit

Janusz Andrzej, Przyborowski Mateusz, Biczyk Piotr, Ślęzak Dominik

Annals of Computer Science and Information Systems

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2020

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Vol. 21

77--80

EN

FedCSIS 2020 Data Mining Challenge: Network Device Workload Prediction was the seventh edition of the international data mining competition organized at Knowledge Pit, in association with the Conference on Computer Science and Information Systems. The main goal was to answer the question of whether it is possible to reliably predict workload-related characteristics of monitored network devices based on historical readings. We describe the scope and explain the motivation for this challenge. We also analyze solutions uploaded by the most successful participants and investigate prediction errors which had the greatest influence on the results. Finally, we describe our baseline solution to the considered problem, which turned out to be the most reliable in the final evaluation.

2

On effectiveness of human cell nuclei detection dependin

Pławiak-Mowna A., Mazurkiewicz M.

Przegląd Elektrotechniczny

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2018

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R. 94, nr 1

77--80

EN

The paper presents results of research on effectiveness of automated detection of human body cells nuclei depending on the digital image color representation used. The problem importance is presented, data representation and processing problems are discussed. The standardized machine vision-based nuclei detection procedure is proposed. Nuclei detection effectiveness measurement algorithm is presented and results are discussed. The conclusion is drawn and future work areas are indicated.

PL

W artykule przedstawiono wyniki badań skuteczności zautomatyzowanego wykrywania jąder komórkowych, w zależności od zastosowanej reprezentacji koloru przetwarzanego obrazu. Przedstawiono problemy związane z przetwarzaniem cyfrowych obrazów medycznych. Zaproponowano ujednoliconą procedurę komputerowego przetwarzania obrazu. Przedstawiono algorytm pomiaru skuteczności wykrywania jąder komórkowych w zależności od zastosowanej przestrzeni barw. Omówiono wyniki, sformułowano wnioski i wskazano przyszłe obszary badań.

3

Detekcja jąder komórkowych w obrazach biomedycznych z uwzględnieniem kodowania barw

Pławiak-Mowna A., Mazurkiewicz M.

Przegląd Elektrotechniczny

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2018

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R. 94, nr 12

246--249

PL

W artykule omówiono proces ekstrakcji parametrów morfometrycznych cyfrowych obrazów histopatologicznych na przykładzie obrazów raka piersi. Wskazano empirycznie wyznaczoną reprezentację kolorów do skutecznego zautomatyzowanego wykrywania jąder komórkowych. Przedstawiono problematykę związaną z komputerowym wspomaganiem rozpoznawania obrazów biomedycznych. Przedstawiono, zapisane w pliku csv wyniki dla przetworzonych i rozpoznanych jąder komórkowych (opis liczbowy struktur i obiektów morfologicznych). Wskazano kierunki dalszych.

EN

The paper presents process of morphometric parameters extraction of the digital biomedical image of breast cancer. There was present empirical determination of most effective color channel for automated detection of cell nuclei. The problem of computer-aided biomedical image recognition are presented. The results obtained for processed and properly recognized cell nuclei was presented. All features (numerical description of morphological structures and objects) was stored in the csv file. The future work areas are indicated.

4

A color image segmentation method based on seeded region growing and visual attention

Ouerhani N., Archip N., Huegli H., Erard P.

Image Processing & Communications

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2002

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Vol. 8, no 1

3-11

EN

This paper reports a color image segmentation method based on a seeded region growing technique (SRG) and guided by a saliency-based visual attention algorithm. Inspired by biological vision the purely data-driven model of visual attention is built around the feature, conspicuity and saliency maps. Using chromatic as well as unchromatic scene features, it, automatically, generates a set of regions-of-interest (ROIs), which represent the most visually-salient locations of the image. The automatically selected points are then used as seeds by the region growing algorithm to segment the conspicuous parts of the scene, using a color homogeneity criterion. A snakes-based technique is then used to improve the contours of the segmented regions. The results reported in this paper clearly shoe the effectiveness of the considered model of visual attention to detect the salient locations in color images.

5

Watermarking for images based on color manipulation and block subdivision

Battiato S., Castorina A.

Image Processing & Communications

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2000

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Vol. 6, no 1-2

29-38

EN

In this paper we present a new watermarking scheme for color images. The method represents an improvement and a loose variation of the work done in [l, 2], where the authors proposed to alter the colors of a given image in an imperceptible way. Despite the theoretical accuracy of the method, an intensive testing has shown the weakness against some common image processing techniques in particular: JPEG compression, scaling and low-pass filtering. Experimental results will be produced, in order to demonstrate the validity of our new approach.