يعرض 1 - 20 نتائج من 64 نتيجة بحث عن '(((("element data algorithm") OR ("defect detection algorithm"))) OR ("neural coding algorithm"))', وقت الاستعلام: 0.36s تنقيح النتائج
  1. 1

    Mosaic dataset augmentation. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
  2. 2
  3. 3

    Three types of loss curves. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
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  5. 5

    The structure of the Res2Block module. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
  6. 6

    The structure of the BiFPN. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
  7. 7

    Randomly adding Gaussian white noise. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
  8. 8

    Algorithm detection performance. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
  9. 9
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  11. 11

    Results of the bearing defect detection. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
  12. 12

    Bearing defect dataset. حسب Kangning Li (6069629)

    منشور في 2024
    الموضوعات:
  13. 13

    Results of the comparative experiment. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"
  14. 14

    Comparison of attention mechanisms. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"
  15. 15

    Results of ablation experiments. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"
  16. 16

    Comparison of attention mechanisms. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"
  17. 17

    Experimental environment configuration. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"
  18. 18

    Model comparison experiments. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"
  19. 19

    Comparison results of the loss functions. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"
  20. 20

    Insulator dataset data enhancement. حسب Jia Li (160557)

    منشور في 2025
    "…To address this problem, this paper proposes a YOLOv8-based insulator defect detection algorithm, YOLOv8-SSF. Firstly, SimAM (parameter-free attention mechanism) is included in the algorithm’s backbone network, which improves the ability to focus on critical features while maintaining a lightweight model. …"