Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significantly lower » significantly higher (Expand Search)
lower decrease » larger decrease (Expand Search), linear decrease (Expand Search), teer decrease (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significantly lower » significantly higher (Expand Search)
lower decrease » larger decrease (Expand Search), linear decrease (Expand Search), teer decrease (Expand Search)
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1781
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1782
Principal component analysis of soil parameters.
Published 2025“…Soil samples were collected from three topography positions (lower, middle, and upper slope locations) and on both soil samplings (0–20 cm and 20–40 cm). …”
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1783
General data comparison.
Published 2024“…The mortality rate during the pandemic (0.13%) was lower than after the pandemic (2.45%).</p><p>Conclusion</p><p>The COVID-19 pandemic has impacted trauma patients admitted through the emergency department, with increases in the proportion of male and younger patients, surgical cases, and a decrease in mortality rates during the pandemic.…”
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1784
The epidemic period group.
Published 2024“…The mortality rate during the pandemic (0.13%) was lower than after the pandemic (2.45%).</p><p>Conclusion</p><p>The COVID-19 pandemic has impacted trauma patients admitted through the emergency department, with increases in the proportion of male and younger patients, surgical cases, and a decrease in mortality rates during the pandemic.…”
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1785
Original data.
Published 2024“…The mortality rate during the pandemic (0.13%) was lower than after the pandemic (2.45%).</p><p>Conclusion</p><p>The COVID-19 pandemic has impacted trauma patients admitted through the emergency department, with increases in the proportion of male and younger patients, surgical cases, and a decrease in mortality rates during the pandemic.…”
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1786
Post-epidemic group.
Published 2024“…The mortality rate during the pandemic (0.13%) was lower than after the pandemic (2.45%).</p><p>Conclusion</p><p>The COVID-19 pandemic has impacted trauma patients admitted through the emergency department, with increases in the proportion of male and younger patients, surgical cases, and a decrease in mortality rates during the pandemic.…”
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1787
Comparison of admissions by department.
Published 2024“…The mortality rate during the pandemic (0.13%) was lower than after the pandemic (2.45%).</p><p>Conclusion</p><p>The COVID-19 pandemic has impacted trauma patients admitted through the emergency department, with increases in the proportion of male and younger patients, surgical cases, and a decrease in mortality rates during the pandemic.…”
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1788
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1789
Study sample.
Published 2025“…One increased National Institute of Health Stroke Scale (NIHSS) score decreased adjusted BI scores by 3.6.</p><p>Conclusion</p><p>The time after discharge, gender, stroke subtype, and stroke severity are significant factors affecting functional outcomes after a stroke. …”
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1790
The overall framework of CARAFE.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1791
KPD-YOLOv7-GD network structure diagram.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1792
Comparison experiment of accuracy improvement.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1793
Comparison of different pruning rates.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1794
Comparison of experimental results at ablation.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1795
Result of comparison of different lightweight.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1796
DyHead Structure.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1797
The parameters of the training phase.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1798
Structure of GSConv network.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1799
Comparison experiment of accuracy improvement.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”
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1800
Improved model distillation structure.
Published 2025“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”