Showing 4,941 - 4,960 results of 18,343 for search 'significantly ((((((larger decrease) OR (a decrease))) OR (teer decrease))) OR (mean decrease))', query time: 0.60s Refine Results
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    Simulation datasets. by Xiao Mo (2430355)

    Published 2025
    “…These results offer significant theoretical guidance for the design and improvement of needle-free injection.…”
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  11. 4951

    SEM morphology of power: (a)17−4PH; (b)TiC. by Dian Yu Luo (22656111)

    Published 2025
    “…Compared to the commercial blade, the wear of the laser-cladded blade was decreased by 67%. This study successfully applied wear-resistant laser cladding coatings on the surface of harvester blades with small substrate thickness, significantly extending their service life.…”
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  13. 4953

    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. …”
  14. 4954

    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. …”
  15. 4955

    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. …”
  16. 4956

    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. …”
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    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. …”
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    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. …”
  19. 4959

    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. …”
  20. 4960

    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. …”