يعرض 1 - 14 نتائج من 14 نتيجة بحث عن '(((( spatial modeling algorithm ) OR ( data boosting algorithm ))) OR ( element data algorithm ))~', وقت الاستعلام: 0.46s تنقيح النتائج
  1. 1

    YOLOv8 model architecture diagram. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  2. 2

    Ablation study visualization results. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  3. 3

    Experimental parameter configuration. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  4. 4

    FLMP-YOLOv8 identification results. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  5. 5

    C2f structure. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  6. 6

    Experimental environment configuration. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  7. 7

    Ablation experiment results table. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  8. 8

    YOLOv8 identification results. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  9. 9

    LSKA module structure diagram. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  10. 10

    Comparison of mAP curves in ablation experiments. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  11. 11

    FarsterBlock structure. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  12. 12

    Sample augmentation and annotation illustration. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  13. 13

    FLMP-YOLOv8 architecture diagram. حسب Xiaozhou Feng (2918222)

    منشور في 2025
    "…Second, a Large Separable Kernel Attention (LSKA) mechanism is incorporated into the Spatial Pyramid Pooling-Fast (SPPF) module of YOLOv8, improving the model’s ability to perceive fine details of diseased trees and reducing interference from other elements in the forest. …"
  14. 14

    Machine Learning Correlation of Electron Micrographs and ToF-SIMS for the Analysis of Organic Biomarkers in Mudstone حسب Michael J. Pasterski (11726741)

    منشور في 2024
    "…We use unsupervised ML on scanning electron microscopy–electron dispersive spectroscopy (SEM-EDS) measurements to define compositional categories based on differences in elemental abundances. We then test the ability of four ML algorithmsk-nearest neighbors (KNN), recursive partitioning and regressive trees (RPART), eXtreme gradient boost (XGBoost), and random forest (RF)to classify the ToF-SIM spectra using (1) the categories assigned via SEM-EDS, (2) organic and inorganic labels assigned via SEM-EDS, and (3) the presence or absence of detectable steranes in ToF-SIMS spectra. …"