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    Wyświetlanie 1-11 z 11
    Tytuł:
    Fusion of feature selection methods in gene recognition
    Autorzy:
    Gil, Fabian
    Osowski, Stanislaw
    Powiązania:
    https://bibliotekanauki.pl/articles/2128155.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    diagnostic features
    selection methods
    genes
    recognition
    biomarkers
    funkcja diagnostyczna
    metody selekcji
    geny
    rozpoznanie
    biomarkery
    Opis:
    The paper presents the fusion approach of different feature selection methods in pattern recognition problems. The following methods are examined: nearest component analysis, Fisher discriminant criterion, refiefF method, stepwise fit, Kolmogorov-Smirnov criteria, T2-test, Kruskall-Wallis test, feature correlation with class, and SVM recursive feature elimination. The sensitivity to the noisy data as well as the repeatability of the most important features are studied. Based on this study, the best selection methods are chosen and applied in the process of selection of the most important genes and gene sequences in a dataset of gene expression microarray in prostate and ovarian cancers. The results of their fusion are presented and discussed. The small selected set of such genes can be treated as biomarkers of cancer.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e136748, 1--8
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Deep Classifiers and Wavelet Transformation for Fake Image Detection
    Autorzy:
    Osowski, Stanislaw
    Golgowski, Maciej
    Powiązania:
    https://bibliotekanauki.pl/articles/27312950.pdf
    Data publikacji:
    2023
    Wydawca:
    Instytut Łączności - Państwowy Instytut Badawczy
    Tematy:
    continuous wavelet transform
    convolutional neural
    networks
    deep fake
    ensemble of classifiers
    Opis:
    The paper presents a computer system for detecting deep fake images in videos. The system is based on continuous wavelet transformation combined with a set of classifiers composed of a few convolutional neural networks of diversified architectures. Three different forms of forged images taken from the FaceForensics++ database are considered in numerical experiments. The results of experiments involving the proposed system have shown good performance in comparison to other current approaches to this particular problem.
    Źródło:
    Journal of Telecommunications and Information Technology; 2023, 4; 1--8
    1509-4553
    1899-8852
    Pojawia się w:
    Journal of Telecommunications and Information Technology
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Fusion of feature selection methods in gene recognition
    Autorzy:
    Gil, Fabian
    Osowski, Stanislaw
    Powiązania:
    https://bibliotekanauki.pl/articles/2173571.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    diagnostic features
    selection methods
    genes
    recognition
    biomarkers
    funkcja diagnostyczna
    metody selekcji
    geny
    rozpoznanie
    biomarkery
    Opis:
    The paper presents the fusion approach of different feature selection methods in pattern recognition problems. The following methods are examined: nearest component analysis, Fisher discriminant criterion, refiefF method, stepwise fit, Kolmogorov-Smirnov criteria, T2-test, Kruskall-Wallis test, feature correlation with class, and SVM recursive feature elimination. The sensitivity to the noisy data as well as the repeatability of the most important features are studied. Based on this study, the best selection methods are chosen and applied in the process of selection of the most important genes and gene sequences in a dataset of gene expression microarray in prostate and ovarian cancers. The results of their fusion are presented and discussed. The small selected set of such genes can be treated as biomarkers of cancer.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e136748
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Ensemble of classifiers based on CNN for increasing generalization ability in face image recognition
    Autorzy:
    Szmurło, Robert
    Osowski, Stanisław
    Powiązania:
    https://bibliotekanauki.pl/articles/2173680.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    CNN
    ensemble of classifiers
    face recognition
    feature selection
    convolutional neural networks
    splotowe sieci neuronowe
    zespół klasyfikatorów
    rozpoznawanie twarzy
    wybór funkcji
    Opis:
    The paper considers the problem of increasing the generalization ability of classification systems by creating an ensemble of classifiers based on the CNN architecture. Different structures of the ensemble will be considered and compared. Deep learning fulfills an important role in the developed system. The numerical descriptors created in the last locally connected convolution layer of CNN flattened to the form of a vector, are subjected to a few different selection mechanisms. Each of them chooses the independent set of features, selected according to the applied assessment techniques. Their results are combined with three classifiers: softmax, support vector machine, and random forest of the decision tree. All of them do simultaneously the same classification task. Their results are integrated into the final verdict of the ensemble. Different forms of arrangement of the ensemble are considered and tested on the recognition of facial images. Two different databases are used in experiments. One was composed of 68 classes of greyscale images and the second of 276 classes of color images. The results of experiments have shown high improvement of class recognition resulting from the application of the properly designed ensemble.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e141004
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Ensemble of classifiers based on deep learning for medical image recognition
    Autorzy:
    Gil, Fabian
    Osowski, Stanisław
    Świderski, Bartosz
    Słowińska, Monika
    Powiązania:
    https://bibliotekanauki.pl/articles/2203370.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    breast cancer
    CNN
    deep learning
    ensemble of classifiers
    feature selection
    melanoma
    Opis:
    The paper presents special forms of an ensemble of classifiers for analysis of medical images based on application of deep learning. The study analyzes different structures of convolutional neural networks applied in the recognition of two types of medical images: dermoscopic images for melanoma and mammograms for breast cancer. Two approaches to ensemble creation are proposed. In the first approach, the images are processed by a convolutional neural network and the flattened vector of image descriptors is subjected to feature selection by applying different selection methods. As a result, different sets of a limited number of diagnostic features are generated. In the next stage, these sets of features represent input attributes for the classical classifiers: support vector machine, a random forest of decision trees, and softmax. By combining different selection methods with these classifiers an ensemble classification system is created and integrated by majority voting. In the second approach, different structures of convolutional neural networks are directly applied as the members of the ensemble. The efficiency of the proposed classification systems is investigated and compared to medical data representing dermoscopic images of melanoma and breast cancer mammogram images. Thanks to fusion of the results of many classifiers forming an ensemble, accuracy and all other quality measures have been significantly increased for both types of medical images.
    Źródło:
    Metrology and Measurement Systems; 2023, 30, 1; 139--156
    0860-8229
    Pojawia się w:
    Metrology and Measurement Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Tremor characterization using higher-order statistics
    Autorzy:
    Jakubowski, Jacek.
    Chwaleba, Augustyn.
    Krzysztof, Kwiatos.
    Osowski, Stanisław.
    Powiązania:
    Biuletyn Wojskowej Akademii Technicznej 2001, nr 11, s. 47-59
    Data publikacji:
    2001
    Tematy:
    Medycyna diagnostyka
    Analiza spektralna
    Przetwarzanie danych
    Opis:
    Charakterystyka drżeń rąk z wykorzystaniem statystyk wyższych rzędów.
    Rys., tab.; Bibliogr.; Abstr., Rez., streszcz.
    Dostawca treści:
    Bibliografia CBW
    Artykuł
      Wyświetlanie 1-11 z 11

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