Showing 61 - 80 results of 160 for search '(( primary data process optimization algorithm ) OR ( binary cases based optimization algorithm ))*', query time: 0.60s Refine Results
  1. 61

    Proposed CVAE model. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  2. 62

    Proposed methodology. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  3. 63

    Loss vs. Epoch. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  4. 64

    Sample images from the BreakHis dataset. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  5. 65

    Accuracy vs. Epoch. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  6. 66

    Segmentation results of the proposed model. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  7. 67

    S1 Dataset - by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  8. 68

    CSCO’s flowchart. by Afnan M. Alhassan (18349378)

    Published 2024
    “…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”
  9. 69

    Dendrogram of the stock prices. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”
  10. 70

    Descriptive statistics on stock prices. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”
  11. 71

    Correlation heatmap of the principal components. by Muhammad Hilal Alkhudaydi (21560690)

    Published 2025
    “…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”
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  15. 75

    Proposed reinforcement learning architecture. by Enoch Solomon (21416703)

    Published 2025
    “…<div><p>In the realm of game playing, deep reinforcement learning predominantly relies on visual input to map states to actions. The visual data extracted from the game environment serves as the primary foundation for state representation in reinforcement learning agents. …”
  16. 76
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    Inconsistency concept for a triad (2, 5, 3). by Waldemar W. Koczkodaj (22008783)

    Published 2025
    “…The proposed regeneration method emulates three primary phases of a biological process: identifying the most damaged areas (by identifying inconsistencies in the pairwise comparison matrix), cell proliferation (filling in missing data), and stabilization (optimization of global consistency). …”
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