بدائل البحث:
significantly lower » significantly higher (توسيع البحث)
longer decrease » larger decrease (توسيع البحث), largest decrease (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
lower decrease » larger decrease (توسيع البحث), teer decrease (توسيع البحث), we decrease (توسيع البحث)
significantly lower » significantly higher (توسيع البحث)
longer decrease » larger decrease (توسيع البحث), largest decrease (توسيع البحث)
linear decrease » linear increase (توسيع البحث)
lower decrease » larger decrease (توسيع البحث), teer decrease (توسيع البحث), we decrease (توسيع البحث)
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2561
Elephant ethogram grouped by behavioral category.
منشور في 2025"…During the limited contact period, aggressive interactions were positively associated with fGCM concentrations, whereas a longer duration since first introduction was associated with a decrease. …"
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2562
Behavioral data collection summary.
منشور في 2025"…During the limited contact period, aggressive interactions were positively associated with fGCM concentrations, whereas a longer duration since first introduction was associated with a decrease. …"
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2563
Male elephant subjects included in the study.
منشور في 2025"…During the limited contact period, aggressive interactions were positively associated with fGCM concentrations, whereas a longer duration since first introduction was associated with a decrease. …"
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2564
ECC map.
منشور في 2025"…During the limited contact period, aggressive interactions were positively associated with fGCM concentrations, whereas a longer duration since first introduction was associated with a decrease. …"
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2565
Data set.
منشور في 2025"…During the limited contact period, aggressive interactions were positively associated with fGCM concentrations, whereas a longer duration since first introduction was associated with a decrease. …"
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2566
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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2567
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. …"
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2568
Comparison experiment of accuracy improvement.
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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2569
Comparison of different pruning rates.
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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2570
Comparison of experimental results at ablation.
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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2571
Result of comparison of different lightweight.
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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2572
DyHead Structure.
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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2573
The parameters of the training phase.
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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2574
Structure of GSConv network.
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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2575
Comparison experiment of accuracy improvement.
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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2576
Improved model distillation structure.
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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2577
S1 Graphical abstract -
منشور في 2024"…</p><p>Conclusions</p><p>In patients with MVD-STEMI, the incidence of MACEs was lower in FCR than in FIR, and the decrease was particularly significant in the DM cohort. …"
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2578
Procedural characteristics.
منشور في 2024"…</p><p>Conclusions</p><p>In patients with MVD-STEMI, the incidence of MACEs was lower in FCR than in FIR, and the decrease was particularly significant in the DM cohort. …"
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2579
Clinical characteristics.
منشور في 2024"…</p><p>Conclusions</p><p>In patients with MVD-STEMI, the incidence of MACEs was lower in FCR than in FIR, and the decrease was particularly significant in the DM cohort. …"
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2580
Study flowchart.
منشور في 2024"…</p><p>Conclusions</p><p>In patients with MVD-STEMI, the incidence of MACEs was lower in FCR than in FIR, and the decrease was particularly significant in the DM cohort. …"