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tests algorithm » best algorithm (Expand Search), tested algorithms (Expand Search), means algorithm (Expand Search)
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processing algorithm » modeling algorithm (Expand Search), routing algorithm (Expand Search), tracking algorithm (Expand Search)
method algorithm » network algorithm (Expand Search), means algorithm (Expand Search), mean algorithm (Expand Search)
elements method » element method (Expand Search)
data processing » image processing (Expand Search)
tests algorithm » best algorithm (Expand Search), tested algorithms (Expand Search), means algorithm (Expand Search)
square tests » square test (Expand Search)
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The run time for each algorithm in seconds.
Published 2025“…Finally, we use the Laplace approximation to determine a lower bound for the out-of-sample prediction error and derive a scalable expression for the marginal variance of each prediction. These methods are tested on both real and synthetic data, with the former taken from a network of air quality monitoring stations across California. …”
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Coefficient of each parameter after assessing partial least squares regression to average ROI area.
Published 2024Subjects: “…morphological image processing…”
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Noise reduction on testing sets from STEAD.
Published 2025“…We propose a novel seismic random noise suppression method based on enhanced variational mode decomposition (VMD) with grey wolf optimization (GWO) algorithm, which applies the envelope entropy to evaluate the wolf individual fitness, determine the grey wolf hierarchy, and obtain the optimized key elements <i><i>K</i></i> and <i>α</i> in VMD. …”
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Table 1_Intra- and inter-rater reliability in log volume estimation based on LiDAR data and shape reconstruction algorithms: a case study on poplar logs.docx
Published 2025“…Computer-based algorithms like Poisson interpolation and Random Sampling and Consensus (RANSAC) are commonly used to extract volume data from LiDAR point clouds, and comparative studies have tested these algorithms for accuracy. …”
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