يعرض 181 - 200 نتائج من 954 نتيجة بحث عن '(( algorithm python function ) OR ( ((algorithm python) OR (algorithm both)) function ))*', وقت الاستعلام: 0.28s تنقيح النتائج
  1. 181

    Ablation study on the RSOD dataset. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  2. 182

    Structure and working principle of LI-YOLOv8. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  3. 183

    C2f-E improvement process. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  4. 184

    Structure of Detect and GP-Detect. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  5. 185

    YOLOv8 structure and working principle. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  6. 186

    Improvement of CBS to CBR process. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  7. 187

    EMA attention mechanism working principle. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  8. 188

    Ablation study on the NWPU VHR-10 dataset. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  9. 189

    GSConv working principle. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  10. 190

    PR comparison on NWPU VHR-10 dataset. حسب Pingping Yan (462509)

    منشور في 2025
    "…Using YOLOv8n as the baseline algorithm, the activation function SiLU in the CBS at the backbone network’s SPPF is replaced with ReLU, which reduces interdependencies among parameters. …"
  11. 191

    Data Sheet 1_IGSA-SAC: a novel approach for intrusion detection using improved gravitational search algorithm and soft actor-critic.docx حسب Lizhong Jin (20991293)

    منشور في 2025
    "…On the AWID dataset, IGSA-SAC surpasses 98.9% in both accuracy and F1-score, outperforming existing intrusion detection algorithms.…"
  12. 192

    Noninvasive Diagnosis of Early-Stage Chronic Kidney Disease and Monitoring of the Hemodialysis Process in Clinical Practice via Exhaled Breath Analysis Using an Ultrasensitive Flex... حسب Xin Zhao (71840)

    منشور في 2025
    "…With the assistance of a pattern recognition algorithm , the early diagnosis of CKD was achieved by the sensor, with PCA being used due to sensor’s cross-sensitivity to CKD biomarkers. …"
  13. 193

    Noninvasive Diagnosis of Early-Stage Chronic Kidney Disease and Monitoring of the Hemodialysis Process in Clinical Practice via Exhaled Breath Analysis Using an Ultrasensitive Flex... حسب Xin Zhao (71840)

    منشور في 2025
    "…With the assistance of a pattern recognition algorithm , the early diagnosis of CKD was achieved by the sensor, with PCA being used due to sensor’s cross-sensitivity to CKD biomarkers. …"
  14. 194

    Noninvasive Diagnosis of Early-Stage Chronic Kidney Disease and Monitoring of the Hemodialysis Process in Clinical Practice via Exhaled Breath Analysis Using an Ultrasensitive Flex... حسب Xin Zhao (71840)

    منشور في 2025
    "…With the assistance of a pattern recognition algorithm , the early diagnosis of CKD was achieved by the sensor, with PCA being used due to sensor’s cross-sensitivity to CKD biomarkers. …"
  15. 195

    Noninvasive Diagnosis of Early-Stage Chronic Kidney Disease and Monitoring of the Hemodialysis Process in Clinical Practice via Exhaled Breath Analysis Using an Ultrasensitive Flex... حسب Xin Zhao (71840)

    منشور في 2025
    "…With the assistance of a pattern recognition algorithm , the early diagnosis of CKD was achieved by the sensor, with PCA being used due to sensor’s cross-sensitivity to CKD biomarkers. …"
  16. 196

    Noninvasive Diagnosis of Early-Stage Chronic Kidney Disease and Monitoring of the Hemodialysis Process in Clinical Practice via Exhaled Breath Analysis Using an Ultrasensitive Flex... حسب Xin Zhao (71840)

    منشور في 2025
    "…With the assistance of a pattern recognition algorithm , the early diagnosis of CKD was achieved by the sensor, with PCA being used due to sensor’s cross-sensitivity to CKD biomarkers. …"
  17. 197
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  19. 199

    Hyperparameters of different datasets. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"
  20. 200

    Results of different models. حسب GaoXiang Zhao (21499525)

    منشور في 2025
    "…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …"