بدائل البحث:
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
element control » element controls (توسيع البحث), element content (توسيع البحث), dependent control (توسيع البحث)
source coding » source code (توسيع البحث), source codes (توسيع البحث)
method algorithm » network algorithm (توسيع البحث), means algorithm (توسيع البحث), mean algorithm (توسيع البحث)
coding algorithm » cosine algorithm (توسيع البحث), modeling algorithm (توسيع البحث), finding algorithm (توسيع البحث)
element control » element controls (توسيع البحث), element content (توسيع البحث), dependent control (توسيع البحث)
source coding » source code (توسيع البحث), source codes (توسيع البحث)
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Performance comparison of MFPSP with existing predictors on independent test data.
منشور في 2024الموضوعات: -
183
Ablation study visualization results.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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184
Experimental parameter configuration.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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185
FLMP-YOLOv8 identification results.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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186
C2f structure.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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187
Experimental environment configuration.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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188
Ablation experiment results table.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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189
YOLOv8 identification results.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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190
LSKA module structure diagram.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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191
Comparison of mAP curves in ablation experiments.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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192
FarsterBlock structure.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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193
Sample augmentation and annotation illustration.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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194
YOLOv8 model architecture diagram.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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195
FLMP-YOLOv8 architecture diagram.
منشور في 2025"…To address data collection challenge, this paper proposes a novel feature recognition and detection method for pine wilt disease-infected trees based on an FLMP-YOLOv8 algorithm. …"
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196
Model’s measure methods.
منشور في 2025"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"
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197
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198
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Elements: Multiparticle collision dynamics simulations of mesoscale hydrodynamic interactions in complex soft materials and environments
منشور في 2025"…The primary outcome is open-source software that will supplant private, in-house codes currently used by different researchers, thereby enhancing the transparency and reproducibility of MPCD simulations.…"