يعرض 3,161 - 3,180 نتائج من 9,300 نتيجة بحث عن 'significantly ((((((lower decrease) OR (teer decrease))) OR (we decrease))) OR (linear decrease))', وقت الاستعلام: 0.70s تنقيح النتائج
  1. 3161

    Defect-Triggered Reversible Phase Transformation for Boosting Electrochemical Performance of Coordination Polymers حسب Yixiu Xu (11166860)

    منشور في 2024
    "…Contrary to this common sense, here we demonstrate that both implanting defects and eliminating defects can significantly boost the specific capacitance of the defect-engineered CPs (DECPs), which are about 1.23 and 1.62 times that of the pristine CP, respectively, without loss of rate capability even after 10,000 charge–discharge cycles. …"
  2. 3162

    Defect-Triggered Reversible Phase Transformation for Boosting Electrochemical Performance of Coordination Polymers حسب Yixiu Xu (11166860)

    منشور في 2024
    "…Contrary to this common sense, here we demonstrate that both implanting defects and eliminating defects can significantly boost the specific capacitance of the defect-engineered CPs (DECPs), which are about 1.23 and 1.62 times that of the pristine CP, respectively, without loss of rate capability even after 10,000 charge–discharge cycles. …"
  3. 3163

    The overall framework of CARAFE. حسب Zhongjian Xie (4633099)

    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. …"
  4. 3164

    KPD-YOLOv7-GD network structure diagram. حسب Zhongjian Xie (4633099)

    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. …"
  5. 3165

    Comparison experiment of accuracy improvement. حسب Zhongjian Xie (4633099)

    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. …"
  6. 3166

    Comparison of different pruning rates. حسب Zhongjian Xie (4633099)

    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. …"
  7. 3167

    Comparison of experimental results at ablation. حسب Zhongjian Xie (4633099)

    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. …"
  8. 3168

    Result of comparison of different lightweight. حسب Zhongjian Xie (4633099)

    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. …"
  9. 3169

    DyHead Structure. حسب Zhongjian Xie (4633099)

    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. …"
  10. 3170

    The parameters of the training phase. حسب Zhongjian Xie (4633099)

    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. …"
  11. 3171

    Structure of GSConv network. حسب Zhongjian Xie (4633099)

    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. …"
  12. 3172

    Comparison experiment of accuracy improvement. حسب Zhongjian Xie (4633099)

    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. …"
  13. 3173

    Improved model distillation structure. حسب Zhongjian Xie (4633099)

    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. …"
  14. 3174

    S1 Graphical abstract - حسب Huimin Xian (20390006)

    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. …"
  15. 3175

    Procedural characteristics. حسب Huimin Xian (20390006)

    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. …"
  16. 3176

    Clinical characteristics. حسب Huimin Xian (20390006)

    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. …"
  17. 3177

    Study flowchart. حسب Huimin Xian (20390006)

    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. …"
  18. 3178

    Data. حسب Huimin Xian (20390006)

    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. …"
  19. 3179

    Excel data extraction. حسب Berihun Agegn Mengistie (18781020)

    منشور في 2025
    "…Early detection and treatment of precancerous cervical lesions and human papillomavirus (HPV) infection are strongly advised to decrease the incidence of cervical cancer and death. …"
  20. 3180

    The upper plots show the changes in ZMK for summer and autumn. حسب Peyman Karami (5909264)

    منشور في 2025
    "…<p>Red indicates an increasing trend and green indicates a decreasing trend in fire density. The lower plots show significant increasing and decreasing trends for different biomes in Iran.…"