بدائل البحث:
algorithm fibrin » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm from (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث)
fibrin function » brain function (توسيع البحث)
python function » protein function (توسيع البحث)
algorithm both » algorithm blood (توسيع البحث), algorithm b (توسيع البحث), algorithm etc (توسيع البحث)
both function » body function (توسيع البحث), growth function (توسيع البحث), beach function (توسيع البحث)
algorithm fibrin » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm from (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث)
fibrin function » brain function (توسيع البحث)
python function » protein function (توسيع البحث)
algorithm both » algorithm blood (توسيع البحث), algorithm b (توسيع البحث), algorithm etc (توسيع البحث)
both function » body function (توسيع البحث), growth function (توسيع البحث), beach function (توسيع البحث)
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181
Structure and working principle of LI-YOLOv8.
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. …"
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182
C2f-E improvement process.
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. …"
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183
Structure of Detect and GP-Detect.
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. …"
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184
YOLOv8 structure and working principle.
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. …"
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185
Improvement of CBS to CBR process.
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. …"
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186
EMA attention mechanism working principle.
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. …"
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187
Ablation study on the NWPU VHR-10 dataset.
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. …"
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188
GSConv working principle.
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. …"
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189
PR comparison on NWPU VHR-10 dataset.
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. …"
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190
Data Sheet 1_IGSA-SAC: a novel approach for intrusion detection using improved gravitational search algorithm and soft actor-critic.docx
منشور في 2025"…On the AWID dataset, IGSA-SAC surpasses 98.9% in both accuracy and F1-score, outperforming existing intrusion detection algorithms.…"
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191
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...
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. …"
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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...
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. …"
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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...
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. …"
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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...
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. …"
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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...
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. …"
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196
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197
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198
Hyperparameters of different datasets.
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. …"
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199
Results of different models.
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. …"
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200
Impact of class imbalance.
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. …"