بدائل البحث:
larger decrease » marked decrease (توسيع البحث)
teer decrease » greater decrease (توسيع البحث)
we decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), nn decrease (توسيع البحث)
larger decrease » marked decrease (توسيع البحث)
teer decrease » greater decrease (توسيع البحث)
we decrease » _ decrease (توسيع البحث), a decrease (توسيع البحث), nn decrease (توسيع البحث)
-
1941
Baseline characteristics of participants.
منشور في 2025"…</p><p>Results</p><p>After DRG implementation, the logarithmic mean of total hospitalization expenditures decreased significantly (3.914 ± 0.837 vs. 3.872 ± 1.004), while rates of unplanned readmissions, unplanned reoperations, postoperative complications, and patient complaints within 30 days increased significantly (3.784% vs 4.214%, 0.083% vs 0.166%, 0.207% vs 0.258%, 3.741% vs 5.133%). …"
-
1942
The framework diagram of this study.
منشور في 2025"…</p><p>Results</p><p>After DRG implementation, the logarithmic mean of total hospitalization expenditures decreased significantly (3.914 ± 0.837 vs. 3.872 ± 1.004), while rates of unplanned readmissions, unplanned reoperations, postoperative complications, and patient complaints within 30 days increased significantly (3.784% vs 4.214%, 0.083% vs 0.166%, 0.207% vs 0.258%, 3.741% vs 5.133%). …"
-
1943
-
1944
-
1945
-
1946
-
1947
-
1948
Battery parameters.
منشور في 2025"…The acoustic emission waveforms exhibited a dual-peak characteristic throughout the entire charging and discharging cycles. We observed a pattern in which the time intervals between the waveforms decreased rapidly at first and then stabilized. …"
-
1949
The aging parameters of each group of batteries.
منشور في 2025"…The acoustic emission waveforms exhibited a dual-peak characteristic throughout the entire charging and discharging cycles. We observed a pattern in which the time intervals between the waveforms decreased rapidly at first and then stabilized. …"
-
1950
Minimal data set.
منشور في 2025"…The acoustic emission waveforms exhibited a dual-peak characteristic throughout the entire charging and discharging cycles. We observed a pattern in which the time intervals between the waveforms decreased rapidly at first and then stabilized. …"
-
1951
Experimental lithium-ion batteries.
منشور في 2025"…The acoustic emission waveforms exhibited a dual-peak characteristic throughout the entire charging and discharging cycles. We observed a pattern in which the time intervals between the waveforms decreased rapidly at first and then stabilized. …"
-
1952
Schematic diagram of two time intervals.
منشور في 2025"…The acoustic emission waveforms exhibited a dual-peak characteristic throughout the entire charging and discharging cycles. We observed a pattern in which the time intervals between the waveforms decreased rapidly at first and then stabilized. …"
-
1953
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. …"
-
1954
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. …"
-
1955
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. …"
-
1956
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. …"
-
1957
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. …"
-
1958
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. …"
-
1959
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. …"
-
1960
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. …"