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Wyszukujesz frazę "Korytkowski, Marcin" wg kryterium: Autor


Wyświetlanie 1-2 z 2
Tytuł:
A novel method for invariant image reconstruction
Autorzy:
Pawlak, Mirosław
Panesar, Gurmukh Singh
Korytkowski, Marcin
Powiązania:
https://bibliotekanauki.pl/articles/2031146.pdf
Data publikacji:
2021
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
object representation
invariant features
symmetry
radial orthogonal moments
continuous symmetry
ridge regression
Opis:
In this paper we propose a novel method for invariant image reconstruction with the properly selected degree of symmetry. We make use of Zernike radial moments to represent an image due to their invariance properties to isometry transformations and the ability to uniquely represent the salient features of the image. The regularized ridge regression estimation strategy under symmetry constraints for estimating Zernike moments is proposed. This extended regularization problem allows us to enforces the bilateral symmetry in the reconstructed object. This is achieved by the proper choice of two regularization parameters controlling the level of reconstruction accuracy and the acceptable degree of symmetry. As a byproduct of our studies we propose an algorithm for estimating an angle of the symmetry axis which in turn is used to determine the possible asymmetry present in the image. The proposed image recovery under the symmetry constraints model is tested in a number of experiments involving image reconstruction and symmetry estimation.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2021, 11, 1; 69-80
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficient image retrieval by fuzzy rules from boosting and metaheuristic
Autorzy:
Korytkowski, Marcin
Senkerik, Roman
Scherer, Magdalena M.
Angryk, Rafal A.
Kordos, Miroslaw
Siwocha, Agnieszka
Powiązania:
https://bibliotekanauki.pl/articles/91856.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
image retrieval
fuzzy rules
local image features
pobieranie obrazu
lokalne funkcje obrazu
Opis:
Fast content-based image retrieval is still a challenge for computer systems. We present a novel method aimed at classifying images by fuzzy rules and local image features. The fuzzy rule base is generated in the first stage by a boosting procedure. Boosting meta-learning is used to find the most representative local features. We briefly explore the utilization of metaheuristic algorithms for the various tasks of fuzzy systems optimization. We also provide a comprehensive description of the current best-performing DISH algorithm, which represents a powerful version of the differential evolution algorithm with effective embedded mechanisms for stronger exploration and preservation of the population diversity, designed for higher dimensional and complex optimization tasks. The algorithm is used to fine-tune the fuzzy rule base. The fuzzy rules can also be used to create a database index to retrieve images similar to the query image fast. The proposed approach is tested on a state-of-the-art image dataset and compared with the bag-of-features image representation model combined with the Support Vector Machine classification. The novel method gives a better classification accuracy, and the time of the training and testing process is significantly shorter.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 1; 57-69
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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