بدائل البحث:
greater decrease » greatest decrease (توسيع البحث), greater increase (توسيع البحث), greater disease (توسيع البحث)
gap decrease » a decrease (توسيع البحث), gain decreased (توسيع البحث), step decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), gy decreased (توسيع البحث)
greater decrease » greatest decrease (توسيع البحث), greater increase (توسيع البحث), greater disease (توسيع البحث)
gap decrease » a decrease (توسيع البحث), gain decreased (توسيع البحث), step decrease (توسيع البحث)
nn decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), gy decreased (توسيع البحث)
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Flow chart of research object screening.
منشور في 2025"…Notably, these associations were significant only in non-cancer populations (testosterone: OR=0.97, P < 0.001; estradiol: OR=1.64, P < 0.001), and generally absent in cancer patients except for older cancer patients (≥60 years) where testosterone maintained a significant negative correlation with ALI (OR=0.96, P = 0.020). …"
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The loss of bone in the femoral distal epiphysis is affected by housing type and weightlessness conditions in microgravity.
منشور في 2025"…(F) Conn.D is decreased in FL. Data shown are the mean ± standard deviation with a scatter plot (ns: non-significant, * : p < 0.033, **: p < 0.002, ***: p < 0.0002). …"
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The overall framework of CARAFE.
منشور في 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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KPD-YOLOv7-GD network structure diagram.
منشور في 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. …"