بدائل البحث:
greater decrease » greatest decrease (توسيع البحث), greater increase (توسيع البحث), greater disease (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
we decrease » _ decrease (توسيع البحث), nn decrease (توسيع البحث), mean decrease (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
greater decrease » greatest decrease (توسيع البحث), greater increase (توسيع البحث), greater disease (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
we decrease » _ decrease (توسيع البحث), nn decrease (توسيع البحث), mean decrease (توسيع البحث)
a decrease » _ decrease (توسيع البحث), _ decreased (توسيع البحث), _ decreases (توسيع البحث)
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1741
YOLOV8.
منشور في 2025"…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …"
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1742
Faster-RCNN.
منشور في 2025"…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …"
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1743
Results of ablation experiments.
منشور في 2025"…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …"
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1744
Structure diagram of SPDConv.
منشور في 2025"…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …"
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1745
Wise-IOU regression diagram.
منشور في 2025"…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …"
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1746
Visualization of detection results.
منشور في 2025"…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …"
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1747
Structure diagram of the SE attention mechanism.
منشور في 2025"…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …"
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1748
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1749
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1750
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1751
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1752
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1753
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1754
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1755
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1756
Top 10 significant functional annotations of up-regulated DEGs.
منشور في 2025"…Functional annotations are ordered by decreasing significance, with color indicating significance according to the legend’s color scale, the ratio of genes on the horizontal axis, and DEG count represented by circle size.…"
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1757
Top 10 significant functional annotations of down-regulated DEGs.
منشور في 2025"…Functional annotations are ordered by decreasing significance, with color indicating significance level based on the legend’s color scale, the ratio of genes on the horizontal axis, and DEG count represented by circle size.…"
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1758
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1759
Major hyperparameters of RF-SVR.
منشور في 2024"…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"
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1760
Pseudo code for coupling model execution process.
منشور في 2024"…For instance, the RF-MLPR model achieved a 3.7%–6.5% improvement in the Nash-Sutcliffe efficiency (NSE) metric across four hydrological stations compared to the RF-SVR model. (4) Prediction accuracy decreased with longer forecast periods, with the R<sup>2</sup> value dropping from 0.8886 for a 1-month forecast to 0.6358 for a 12-month forecast, indicating the increasing challenge of long-term predictions due to greater uncertainty and the accumulation of influencing factors over time. (5) The RF-MLPR model outperformed the RF-SVR model, demonstrating a superior ability to capture the complex, nonlinear relationships inherent in the data. …"