Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
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7921
Effects of <i>B</i>.<i>erecta</i> on PD model rats of Depressive-like symptom.
Published 2024Subjects: -
7922
Effects of <i>B</i>. <i>erecta</i> on PD model rats of social interaction test.
Published 2024Subjects: -
7923
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7924
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7925
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7926
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7927
Effects of <i>B</i>. <i>erecta</i> on motor symptom of PD model rats (Rotarod test).
Published 2024Subjects: -
7928
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7929
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7930
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7931
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7932
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7933
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7934
Various parameters characterizing Lb related to lung volume or alveolar surface before, during and after bulk alveolarization (adulthood).
Published 2025“…During alveolarization values remain constant. At pnd 21 a significant decrease compared to 3 days old pups is visible. …”
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7935
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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7936
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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7937
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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7938
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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7939
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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7940
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. …”