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required optimization » guided optimization (Expand Search), resource optimization (Expand Search), feature optimization (Expand Search)
basis optimization » based optimization (Expand Search), task optimization (Expand Search), acid optimization (Expand Search)
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binary space » banach space (Expand Search)
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Showing 1 - 17 results of 17 for search '(( binary space required optimization algorithm ) OR ( binary image basis optimization algorithm ))', query time: 0.54s Refine Results
  1. 1
    Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification

    Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification by Vaibhavi Patel (19843282)

    Published 2024
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  2. 2
    Binary leaf image rotated anti-clock wise from the origin degree to 40<sup><i>o</i></sup>, 80<sup><i>o</i></sup>, 120<sup><i>o</i></sup>, and 160<sup><i>o</i></sup> from left to right respectively to verify rotation invariance with their corresponding curve-fitted data.

    Binary leaf image rotated anti-clock wise from the origin degree to 40<sup><i>o</i></sup>, 80<sup><i>o</i></sup>, 120<sup><i>o</i></sup>, and 160<sup><i>o</i></sup> from left to ri... by Ali Ahmed (2567584)

    Published 2020
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  3. 3
    Homomorphic binary tree.

    Homomorphic binary tree. by Jianhua He (341366)

    Published 2024
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  4. 4
    Overview of the segmentation algorithm.

    Overview of the segmentation algorithm. by Michael C. Robitaille (11949174)

    Published 2022
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  5. 5
    The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus requiring fewer qubits.

    The workflow diagram for the gene expression biomarker study which involve using principal component analysis (PCA) to reduce the number of features (principal components), thus re... by Aninda Astuti (21736334)

    Published 2025
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  6. 6
    Fig 3 -

    Fig 3 - by Ali Ahmed (2567584)

    Published 2020
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  7. 7
    Classification performance after optimization.

    Classification performance after optimization. by Amal H. Alharbi (21755906)

    Published 2025
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  8. 8
    ANOVA test for optimization results.

    ANOVA test for optimization results. by Amal H. Alharbi (21755906)

    Published 2025
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  9. 9
    Wilcoxon test results for optimization.

    Wilcoxon test results for optimization. by Amal H. Alharbi (21755906)

    Published 2025
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  10. 10
    Wilcoxon test results for feature selection.

    Wilcoxon test results for feature selection. by Amal H. Alharbi (21755906)

    Published 2025
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  11. 11
    Feature selection metrics and their definitions.

    Feature selection metrics and their definitions. by Amal H. Alharbi (21755906)

    Published 2025
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  12. 12
    Statistical summary of all models.

    Statistical summary of all models. by Amal H. Alharbi (21755906)

    Published 2025
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  13. 13
    Feature selection results.

    Feature selection results. by Amal H. Alharbi (21755906)

    Published 2025
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  14. 14
    ANOVA test for feature selection.

    ANOVA test for feature selection. by Amal H. Alharbi (21755906)

    Published 2025
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  15. 15
    Classification performance of ML and DL models.

    Classification performance of ML and DL models. by Amal H. Alharbi (21755906)

    Published 2025
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  16. 16
    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment

    Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

    Published 2019
    “…This result reflects the effectiveness of the algorithm, which provides a basis for the effective analysis and processing of image big data.…”
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  17. 17
    PathOlOgics_RBCs Python Scripts.zip

    PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

    Published 2023
    “…</p><p dir="ltr">In terms of classification, a second algorithm was developed and employed to preliminary sort or group the individual cells (after excluding the overlapping cells manually) into different categories using five geometric measurements applied to the extracted contour from each binary image mask (see PathOlOgics_script_2; preliminary shape measurements). …”
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