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Showing 1 - 6 results of 6 for search 'multiple sperm selection algorithm', query time: 0.11s Refine Results
  1. 1
    Average accuracy by feature selection method.

    Average accuracy by feature selection method. by Şafak Kılıç (22227019)

    Published 2025
    “…The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”
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  2. 2
    Average accuracy by feature extraction layer.

    Average accuracy by feature extraction layer. by Şafak Kılıç (22227019)

    Published 2025
    “…The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”
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  3. 3
    Performance analysis by feature extraction layer.

    Performance analysis by feature extraction layer. by Şafak Kılıç (22227019)

    Published 2025
    “…The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”
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  4. 4
    Best model class-wise performance on SMIDS.

    Best model class-wise performance on SMIDS. by Şafak Kılıç (22227019)

    Published 2025
    “…The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”
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  5. 5
    Classifier performance overview.

    Classifier performance overview. by Şafak Kılıç (22227019)

    Published 2025
    “…The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”
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  6. 6
    Best model class-wise performance on HuSHeM.

    Best model class-wise performance on HuSHeM. by Şafak Kılıç (22227019)

    Published 2025
    “…The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”
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