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utilisation algorithm » optimization algorithm (Expand Search), initialization algorithm (Expand Search), optimization algorithms (Expand Search)
resource utilisation » resource utilization (Expand Search), resource allocation (Expand Search), service utilisation (Expand Search)
estimation algorithm » optimization algorithm (Expand Search), optimization algorithms (Expand Search), maximization algorithm (Expand Search)
time resource » situ resource (Expand Search), firm resource (Expand Search), optimize resource (Expand Search)
binary time » binary image (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data pose » data posted (Expand Search), data phase (Expand Search), data base (Expand Search)
Showing 1 - 3 results of 3 for search '(( binary time resource utilisation algorithm ) OR ( binary data pose estimation algorithm ))*', query time: 0.92s Refine Results
  1. 1
    Experimental setup and trajectory estimation methodology.

    Experimental setup and trajectory estimation methodology. by Nouman Javed (16624785)

    Published 2023
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  2. 2
    ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for test data classification results across all folds.

    ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... by G. Christopher Marais (21492084)

    Published 2025
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  3. 3
    GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios

    GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios by Yang Lan (20927512)

    Published 2025
    “…Here, we present GridScopeRodents, a high-resolution global dataset projecting the distribution of 10 rodent genera from 2021 to 2100 under four CMIP6-based Shared Socioeconomic Pathway–Representative Concentration Pathway (SSP–RCP) scenario combinations. Using occurrence data and environmental variable, we employ the Maximum Entropy (MaxEnt) algorithm within the species distribution modeling (SDM) framework to estimate occurrence probability at a spatial resolution of 1/12° (~10 km). …”
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