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Showing 1 - 8 results of 8 for search '(( binary ms based optimization algorithm ) OR ( primary large class optimization algorithm ))', query time: 0.51s Refine Results
  1. 1
    One advantage of our algorithm is that it is not binary in nature.

    One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

    Published 2022
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  2. 2
    Several loop patterns found in binary code.

    Several loop patterns found in binary code. by Alba Pedro-Zapater (8600382)

    Published 2020
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  3. 3
    Sample image for illustration.

    Sample image for illustration. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  4. 4
    Comparison analysis of computation time.

    Comparison analysis of computation time. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  5. 5
    Process flow diagram of CBFD.

    Process flow diagram of CBFD. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  6. 6
    Precision recall curve.

    Precision recall curve. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  7. 7
    Quadratic polynomial in 2D image plane.

    Quadratic polynomial in 2D image plane. by Indhumathi S. (19173013)

    Published 2024
    “…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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  8. 8
    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles

    Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

    Published 2025
    “…</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…”
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