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bayesian optimization » based optimization (Expand Search)
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bayesian optimization » based optimization (Expand Search)
points optimization » joint optimization (Expand Search), process optimization (Expand Search), potency optimization (Expand Search)
sample points » sampling points (Expand Search)
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81
Diagram of the original model confusion matrix.
Published 2025“…A publicly available 5-class object mmWave radar heatmap dataset, including 2,500 annotated images, were selected for data modeling and method evaluation. The results show that the mean average precision (mAP), precision and recall of the S2DB-mmWave YOLOv8n model were 93.1% mAP@0.5, 55.8% mAP@0.5:0.95, 89.4% and 90.6%, respectively, which is 3.3, 1.6, 4.5 and 7.7 percentage points higher than the baseline YOLOv8n network without increasing the parameter count.…”
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83
Big Data Model Building Using Dimension Reduction and Sample Selection
Published 2023“…Furthermore, such subdata cannot be useful to build alternative models because it is not an appropriate representative sample of the full data. In this article, we propose a novel algorithm for better model building and prediction via a process of selecting a “good” training sample. …”
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88
Scatter plots for UTS prediction for heat treated and non-heat treated samples.
Published 2025“…Scatter plots typically display the x-axis as the actual values and the y-axis as the predicted values. Optimally, the data points ought to align precisely along a 45-degree diagonal line, signifying precise predictions where the anticipated values correspond closely to the actual values. …”
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89
Flow diagram of the reachable workspace.
Published 2025“…A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. …”
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90
Size parameters of the 5PUS-RPUR parallel robot.
Published 2025“…A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. …”
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91
Structure diagram of branched PUS with errors.
Published 2025“…A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. …”
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92
PK subproblem 3.
Published 2025“…A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. …”
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93
The two recognized basic PK sub-problems.
Published 2025“…A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. …”
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94
Structure diagram of branched RPUR with errors.
Published 2025“…A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. …”
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95
5PUS-RPUR parallel robot system.
Published 2025“…A sensitivity analysis is performed using the finite difference method to screen for and eliminate error sources with a negligible impact on the moving platform’s pose. Measurement points are then selected uniformly throughout the workspace using the farthest point sampling algorithm. …”
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NZGRC 2022 Poster: Assessing Optimal Flight and Capture Parameters for Post-Thinning Quality Control in Radiata Pine Forest Stands using Unmanned Aerial Vehicles
Published 2022“…These results are expected to inform us of the optimal photogrammetry parameters required for data capture in thinned stands of radiata pine. …”
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98
Dataset for: Optimal Transport, Mean Partition, and Uncertainty Assessment in Cluster Analysis
Published 2019“…We overcome that barrier by aligning clusters via optimal transport. Equipped with this technique, we propose a new algorithm to enhance clustering by any baseline method using bootstrap samples. …”
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Data_Sheet_1_A mixed effects changepoint quantile regression model for longitudinal data with application on COVID-19 data.DOCX
Published 2023“…In addition, the location of the changepoint is estimated using the usual optimization methods.</p>Results and discussion<p>A simulation study shows that the proposed estimation and inferential procedures perform reasonably well in finite samples. …”
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A Composite Likelihood-Based Approach for Change-Point Detection in Spatio-Temporal Processes
Published 2024“…A computationally efficient pruned dynamic programming algorithm is developed for the challenging criterion optimization problem. …”