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Showing 21 - 40 results of 57 for search '(( binary based solution optimization algorithm ) OR ( lens based cell optimization algorithm ))', query time: 1.03s Refine Results
  1. 21
    Simulation parameters.

    Simulation parameters. by Hend Bayoumi (22693738)

    Published 2025
    “…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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  2. 22
    Training losses for N = 10.

    Training losses for N = 10. by Hend Bayoumi (22693738)

    Published 2025
    “…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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  3. 23
    Normalized computation rate for N = 10.

    Normalized computation rate for N = 10. by Hend Bayoumi (22693738)

    Published 2025
    “…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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  4. 24
    Summary of Notations Used in this paper.

    Summary of Notations Used in this paper. by Hend Bayoumi (22693738)

    Published 2025
    “…Hence, an Energy-Harvesting Reinforcement Learning-based Offloading Decision Algorithm (EHRL) is proposed. …”
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  5. 25
    Image4_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF

    Image4_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

    Published 2022
    “…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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  6. 26
    Image1_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF

    Image1_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

    Published 2022
    “…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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  7. 27
    Image3_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF

    Image3_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

    Published 2022
    “…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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  8. 28
    Image2_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF

    Image2_CNN-Based Cell Analysis: From Image to Quantitative Representation.TIF by Cédric Allier (4180903)

    Published 2022
    “…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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  9. 29
    DataSheet1_CNN-Based Cell Analysis: From Image to Quantitative Representation.pdf

    DataSheet1_CNN-Based Cell Analysis: From Image to Quantitative Representation.pdf by Cédric Allier (4180903)

    Published 2022
    “…<p>We present a novel deep learning-based quantification pipeline for the analysis of cell culture images acquired by lens-free microscopy. …”
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  10. 30
    Comparison in terms of the sensitivity.

    Comparison in terms of the sensitivity. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  11. 31
    Parameter sensitivity of BIMGO.

    Parameter sensitivity of BIMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  12. 32
    Details of the medical datasets.

    Details of the medical datasets. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  13. 33
    The flowchart of IMGO.

    The flowchart of IMGO. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  14. 34
    Comparison in terms of the selected features.

    Comparison in terms of the selected features. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  15. 35
    Iterative chart of control factor.

    Iterative chart of control factor. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  16. 36
    Details of 23 basic benchmark functions.

    Details of 23 basic benchmark functions. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  17. 37
    Related researches.

    Related researches. by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  18. 38
    S1 Dataset -

    S1 Dataset - by Ying Li (38224)

    Published 2024
    “…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …”
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  19. 39
    Parameter settings.

    Parameter settings. by Yang Cao (53545)

    Published 2024
    “…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …”
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  20. 40
    Example of simulated calcium imaging dataset.

    Example of simulated calcium imaging dataset. by Virgil Christian Garcia Castillo (19688355)

    Published 2024
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