يعرض 1,741 - 1,760 نتائج من 4,225 نتيجة بحث عن 'significantly ((((((nn decrease) OR (mean decrease))) OR (linear decrease))) OR (teer decrease))', وقت الاستعلام: 0.38s تنقيح النتائج
  1. 1741

    DyHead Structure. حسب Zhongjian Xie (4633099)

    منشور في 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. …"
  2. 1742

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

    منشور في 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. …"
  3. 1743

    Structure of GSConv network. حسب Zhongjian Xie (4633099)

    منشور في 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. …"
  4. 1744

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

    منشور في 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. …"
  5. 1745

    Improved model distillation structure. حسب Zhongjian Xie (4633099)

    منشور في 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. …"
  6. 1746
  7. 1747
  8. 1748
  9. 1749
  10. 1750
  11. 1751
  12. 1752
  13. 1753
  14. 1754
  15. 1755
  16. 1756

    Performance comparison of ML models. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  17. 1757

    Comparative data of different soil samples. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  18. 1758

    Confusion matrix of random forest model. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  19. 1759

    Sensor value scenario for fuzzy logic algorithm. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"
  20. 1760

    Evaluation metrics of selected ML models. حسب Gourab Saha (8987405)

    منشور في 2025
    "…Multi-spectral band images from Landsat-8 satellite images of a chosen land are employed from USGS Earth Resources Observation and Science (EROS) Center for extracting indices that are used for agricultural analysis, determining the vegetation index, water index, and salinity index of that land using K-means. Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. …"