Showing 5,841 - 5,860 results of 18,768 for search 'significantly ((((((we decrease) OR (mean decrease))) OR (a decrease))) OR (observed decrease))', query time: 0.82s Refine Results
  1. 5841
  2. 5842

    Analyses of directed phase lag index (dPLI [44]) for excitatory/inhibitory (E/I) ratios with respect to pyramidal (Pyr) and parvalbumin (PV) populations (<i>A</i>) and Pyr and soma... by Nobuhiko Wagatsuma (494052)

    Published 2025
    “…<p>Black circles and gray pentagons represent the mean values of dPLI from PV to Pyr and from SOM to Pyr populations, respectively. …”
  3. 5843

    SlABCG9 Functioning as a Jasmonic Acid Transporter Influences Tomato Resistance to Botrytis cinerea by Ning Tao (109880)

    Published 2025
    “…Assays using Xenopus oocytes, yeast cell sensitivity, and JA-inhibited primary root growth confirmed that SlABCG9 functions as a JA influx transporter. The knockout mutant lines of <i>SlABCG9</i> showed decreased JA contents, suppressed defense gene <i>PDF1.2</i>’s expression, reduced antioxidant enzyme activity, and severe disease symptoms compared to wild-type controls. …”
  4. 5844

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  5. 5845

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  6. 5846

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  7. 5847

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  8. 5848

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  9. 5849

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  10. 5850

    DyHead Structure. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  11. 5851

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  12. 5852

    Structure of GSConv network. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  13. 5853

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

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  14. 5854

    Improved model distillation structure. by Zhongjian Xie (4633099)

    Published 2025
    “…Firstly, improve the multi-scale feature layer and reduce the complexity of the model. 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. …”
  15. 5855
  16. 5856
  17. 5857
  18. 5858

    Presentation_1_Multifaceted neuroprotective approach of Trolox in Alzheimer's disease mouse model: targeting Aβ pathology, neuroinflammation, oxidative stress, and synaptic dysfunc... by Muhammad Tahir (741682)

    Published 2024
    “…This research study is significant as it aims to assess the neuroprotective properties of vitamin E (VE) analog Trolox in an Aβ<sub>1 − 42</sub>-induced AD mouse model. …”
  19. 5859
  20. 5860

    Ignition delay process shot by high-speed camera. by Lei Bai (631944)

    Published 2025
    “…The evolution of the fractal dimension of the lubricating oil droplet flame shows a trend of first increasing and then slowly decreasing. …”