Showing 4,181 - 4,200 results of 14,170 for search '(( significant decrease decrease ) OR ( significant results decrease ))~', query time: 0.42s Refine Results
  1. 4181
  2. 4182

    MFDPN module. by Bo Tong (2138632)

    Published 2025
    “…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”
  3. 4183

    Detection effect of different sizes. by Bo Tong (2138632)

    Published 2025
    “…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”
  4. 4184

    Radar chart comparing indicators. by Bo Tong (2138632)

    Published 2025
    “…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”
  5. 4185

    MFD-YOLO structure. by Bo Tong (2138632)

    Published 2025
    “…Additionally, structured pruning techniques were applied to the model at varying levels, further reducing computational and parameter loads. Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”
  6. 4186
  7. 4187

    Molecular Insights into the Crystallization of 4’-Hydroxyacetophenone from Water: Solute Aggregation, Liquid–Liquid Phase Separation, and Polymorph Selection by Carlos E. S. Bernardes (7183481)

    Published 2025
    “…As cooling progresses, they become more compact, a process accompanied by a reduction in water content, which is more significant as the solution concentration increases. …”
  8. 4188

    Molecular Insights into the Crystallization of 4’-Hydroxyacetophenone from Water: Solute Aggregation, Liquid–Liquid Phase Separation, and Polymorph Selection by Carlos E. S. Bernardes (7183481)

    Published 2025
    “…As cooling progresses, they become more compact, a process accompanied by a reduction in water content, which is more significant as the solution concentration increases. …”
  9. 4189

    Molecular Insights into the Crystallization of 4’-Hydroxyacetophenone from Water: Solute Aggregation, Liquid–Liquid Phase Separation, and Polymorph Selection by Carlos E. S. Bernardes (7183481)

    Published 2025
    “…As cooling progresses, they become more compact, a process accompanied by a reduction in water content, which is more significant as the solution concentration increases. …”
  10. 4190
  11. 4191

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

    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. …”
  12. 4192

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

    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. …”
  13. 4193
  14. 4194

    Accuracy and loss values of each model. by Hongwei Bai (1447999)

    Published 2025
    “…The global max-pooling layer replaces the fully connected layer, reducing the number of parameters, improving computational efficiency, and lowering the risk of overfitting. Experimental results demonstrate that the proposed model achieves superior performance in fault diagnosis, attaining an accuracy of 99.62%, significantly outperforming traditional CNNs and other benchmark methods.…”
  15. 4195

    Model parameter indicators. by Hongwei Bai (1447999)

    Published 2025
    “…The global max-pooling layer replaces the fully connected layer, reducing the number of parameters, improving computational efficiency, and lowering the risk of overfitting. Experimental results demonstrate that the proposed model achieves superior performance in fault diagnosis, attaining an accuracy of 99.62%, significantly outperforming traditional CNNs and other benchmark methods.…”
  16. 4196

    Classification of bearing data labels. by Hongwei Bai (1447999)

    Published 2025
    “…The global max-pooling layer replaces the fully connected layer, reducing the number of parameters, improving computational efficiency, and lowering the risk of overfitting. Experimental results demonstrate that the proposed model achieves superior performance in fault diagnosis, attaining an accuracy of 99.62%, significantly outperforming traditional CNNs and other benchmark methods.…”
  17. 4197
  18. 4198

    Loading mode. by Maogang Tian (21485116)

    Published 2025
    “…The outer ring of inclined piles in the VIPF significantly enhances structural stiffness through spatial synergy, achieving uniform load distribution and effective redistribution of pile-body internal forces. …”
  19. 4199

    Model and meshes. by Maogang Tian (21485116)

    Published 2025
    “…The outer ring of inclined piles in the VIPF significantly enhances structural stiffness through spatial synergy, achieving uniform load distribution and effective redistribution of pile-body internal forces. …”
  20. 4200

    Shearing forces in the tension zone. by Maogang Tian (21485116)

    Published 2025
    “…The outer ring of inclined piles in the VIPF significantly enhances structural stiffness through spatial synergy, achieving uniform load distribution and effective redistribution of pile-body internal forces. …”