Showing 201 - 220 results of 984 for search '(( algorithm spread function ) OR ( ((algorithm python) OR (algorithm both)) function ))', query time: 0.37s Refine Results
  1. 201

    PR comparison on RSOD dataset. by Pingping Yan (462509)

    Published 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. 202

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

    Published 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. 203

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

    Published 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. 204

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

    Published 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. 205

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

    Published 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. 206

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

    Published 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. 207

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

    Published 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. 208

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

    Published 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. 209

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

    Published 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. 210

    GSConv working principle. by Pingping Yan (462509)

    Published 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. 211

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

    Published 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. …”
  12. 212

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

    Published 2025
    “…On the AWID dataset, IGSA-SAC surpasses 98.9% in both accuracy and F1-score, outperforming existing intrusion detection algorithms.…”
  13. 213

    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... by Xin Zhao (71840)

    Published 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. 214

    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... by Xin Zhao (71840)

    Published 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. 215

    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... by Xin Zhao (71840)

    Published 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. 216

    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... by Xin Zhao (71840)

    Published 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. 217

    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... by Xin Zhao (71840)

    Published 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. …”
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  20. 220

    Hyperparameters of different datasets. by GaoXiang Zhao (21499525)

    Published 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. …”