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processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
estimation algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), detection algorithm (Expand Search)
edge processing » image processing (Expand Search), pre processing (Expand Search), time processing (Expand Search)
binary edge » binary image (Expand Search)
processing optimization » process optimization (Expand Search), process optimisation (Expand Search), routing optimization (Expand Search)
estimation algorithm » optimization algorithms (Expand Search), maximization algorithm (Expand Search), detection algorithm (Expand Search)
edge processing » image processing (Expand Search), pre processing (Expand Search), time processing (Expand Search)
binary edge » binary image (Expand Search)
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Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30.
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Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30.
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The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames.
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CDF of task latency, approximated as the inverse of the achieved computation rate.
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PathOlOgics_RBCs Python Scripts.zip
Published 2023“…This process generated a ground-truth binary semantic segmentation mask and determined the bounding box coordinates (XYWH) for each cell. …”
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Table_1_Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model.docx
Published 2024“…The R-LBP algorithm, an extension of the LBP algorithm, enhances the texture features of citrus fruits at distinct ripeness stages by calculating the coefficient of variation in grayscale values of pixels within a certain range in different directions around the target pixel. …”
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GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios
Published 2025“…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). …”