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Showing 1 - 20 results of 246 for search '(( binary _ feature optimization algorithm ) OR ( binary image learning optimization algorithm ))', query time: 0.58s Refine Results
  1. 1
    Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm

    Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

    Published 2025
    “…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”
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  2. 2
    Feature selection convergence time comparison of various binary metaheuristic algorithms.

    Feature selection convergence time comparison of various binary metaheuristic algorithms. by Amal H. Alharbi (21755906)

    Published 2025
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  3. 3
    Number of features selected for IRBMO vs. other binary algorithms.

    Number of features selected for IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  4. 4
    Sensitivity values of IRBMO vs. other binary algorithms.

    Sensitivity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  5. 5
    Specificity values of IRBMO vs. other binary algorithms.

    Specificity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  6. 6
    Fitness values of IRBMO vs. other binary algorithms.

    Fitness values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  7. 7
    Classification accuracy values of IRBMO vs. other binary algorithms.

    Classification accuracy values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  8. 8
    F-score values of IRBMO vs. other binary algorithms.

    F-score values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

    Published 2025
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  9. 9
    Feature selection ratio results for tested algorithms.

    Feature selection ratio results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  10. 10
    Initial parameter settings for the optimization algorithms.

    Initial parameter settings for the optimization algorithms. by Doaa Sami Khafaga (21463870)

    Published 2025
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  11. 11
    The result of the accuracy of tested algorithms.

    The result of the accuracy of tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  12. 12
    Numerical example for determining the optimal number of clusters in Algorithm 2.

    Numerical example for determining the optimal number of clusters in Algorithm 2. by Yi Wei Tye (22208735)

    Published 2025
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  13. 13
    Bar chart comparing the average fitness values of various feature selection algorithms.

    Bar chart comparing the average fitness values of various feature selection algorithms. by Doaa Sami Khafaga (21463870)

    Published 2025
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  14. 14
    Hyperparameter settings for the optimization algorithms.

    Hyperparameter settings for the optimization algorithms. by Ahmed M. Elshewey (21463867)

    Published 2025
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  15. 15
    The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms.

    The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. by Olaide N. Oyelade (14047002)

    Published 2023
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  16. 16
    a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset.

    a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset. by Nebojsa Bacanin (13932723)

    Published 2022
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  17. 17
    Best fitness value results for tested algorithms.

    Best fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  18. 18
    Mean fitness value results for tested algorithms.

    Mean fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  19. 19
    Standard deviation of fitness value results for tested algorithms.

    Standard deviation of fitness value results for tested algorithms. by Nebojsa Bacanin (13932723)

    Published 2022
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  20. 20
    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale.

    Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. by Tehnan I. A. Mohamed (16846175)

    Published 2023
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