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feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
binary risks » dietary risks (Expand Search), binary mask (Expand Search)
risks driven » risks derived (Expand Search), rivers driven (Expand Search), virus driven (Expand Search)
task feature » based feature (Expand Search), each feature (Expand Search), a feature (Expand Search)
binary task » binary mask (Expand Search)
Showing 21 - 32 results of 32 for search '(( binary risks driven optimization algorithm ) OR ( binary task feature optimization algorithm ))', query time: 0.54s Refine Results
  1. 21
    IRBMO vs. variant comparison adaptation data.

    IRBMO vs. variant comparison adaptation data. by Chenyi Zhu (9383370)

    Published 2025
    “…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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  2. 22
    Flowchart scheme of the ML-based model.

    Flowchart scheme of the ML-based model. by Noshaba Qasmi (20405009)

    Published 2024
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  3. 23
    Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png

    Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

    Published 2025
    “…</p>Results and Discussion<p>Experimental evaluation across varied athlete cohorts demonstrates superior performance in risk stratification accuracy, diagnostic plausibility, and model transparency compared to traditional screening algorithms. …”
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  4. 24
    Sample image for illustration.

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

    Published 2024
    “…<div><p>Feature description is a critical task in Augmented Reality Tracking. …”
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  5. 25
    Comparison analysis of computation time.

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

    Published 2024
    “…<div><p>Feature description is a critical task in Augmented Reality Tracking. …”
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  6. 26
    Process flow diagram of CBFD.

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

    Published 2024
    “…<div><p>Feature description is a critical task in Augmented Reality Tracking. …”
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  7. 27
    Precision recall curve.

    Precision recall curve. by Indhumathi S. (19173013)

    Published 2024
    “…<div><p>Feature description is a critical task in Augmented Reality Tracking. …”
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  8. 28
    Quadratic polynomial in 2D image plane.

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

    Published 2024
    “…<div><p>Feature description is a critical task in Augmented Reality Tracking. …”
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  9. 29
    Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx

    Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx by Çaǧlar Çaǧlayan (12253934)

    Published 2022
    “…We performed threshold optimization for converting predicted probabilities into binary predictions and identified the cut-off maximizing the sum of sensitivity and specificity.…”
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  10. 30
    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP

    Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP by Xiaoyuan Wang (492534)

    Published 2022
    “…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”
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  11. 31
    Models and Dataset

    Models and Dataset by M RN (9866504)

    Published 2025
    “…The algorithm does not rely on predefined control parameters like crossover or mutation rates, which makes it lightweight and easy to implement for various feature selection and optimization tasks.…”
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  12. 32
    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf

    Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

    Published 2020
    “…In this way, for each binary problem, the CSP algorithm produces features to determine if the specific body part is engaged in the task or not. …”
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