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801
YOLOv8n-BWG detection results diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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802
GSConv module structure diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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803
Performance comparison of three loss functions.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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804
mAP0.5 Curves of various models.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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805
Network loss function change diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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806
Comparative diagrams of different indicators.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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807
YOLOv8n structure diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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808
Geometric model of the binocular system.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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809
Enhanced dataset sample images.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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810
Changes in graph parameters over the birth transition.
Published 2024“…<p>(A) Nodes showing significant age-related changes in GE, where red indicates increased GE with age, while blue indicates decreased GE with age. …”
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811
Table 1_Impact of a pharmacist driven antimicrobial stewardship program on inpatient antibiotic consumption in a Chinese Tertiary Hospital: a 5-year retrospective study.xlsx
Published 2025“…Through targeted management, some antibiotics showed trends of increased or decreased usage. The detection rates of Methicillin-Resistant Staphylococcus aureus and Extended-spectrum β-lactamase-producing Escherichia coli did not show a significant decrease.…”
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812
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813
High-Precision Printing Sandwich Flexible Transparent Silver Mesh for Tunable Electromagnetic Interference Shielding Visualization Windows
Published 2024“…Hence, a significant challenge still remains in the realm of metal mesh-based FTCFs to enhance EMI SE while maintaining their original optical transmittance and equivalent material usage. …”
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814
High-Precision Printing Sandwich Flexible Transparent Silver Mesh for Tunable Electromagnetic Interference Shielding Visualization Windows
Published 2024“…Hence, a significant challenge still remains in the realm of metal mesh-based FTCFs to enhance EMI SE while maintaining their original optical transmittance and equivalent material usage. …”
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815
High-Precision Printing Sandwich Flexible Transparent Silver Mesh for Tunable Electromagnetic Interference Shielding Visualization Windows
Published 2024“…Hence, a significant challenge still remains in the realm of metal mesh-based FTCFs to enhance EMI SE while maintaining their original optical transmittance and equivalent material usage. …”
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816
High-Precision Printing Sandwich Flexible Transparent Silver Mesh for Tunable Electromagnetic Interference Shielding Visualization Windows
Published 2024“…Hence, a significant challenge still remains in the realm of metal mesh-based FTCFs to enhance EMI SE while maintaining their original optical transmittance and equivalent material usage. …”
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817
The expression of PAX7 and MYOD1 correlate with differential expression of diverse chemokines in HuMuSC.
Published 2025“…<p><b>(a)</b> Quantification of protein expression for PAX7+ and MYOD1 positive HuMuSC at day 0, 3 and 6 in vitro, showing an inverse correlation as progressively PAX7 expression decreases and MYOD1 expression increases in HuMuSC as they activate <i>in vitro</i>. …”
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818
<i>map3k1</i> inhibition causes <i>ovo+</i> eye progenitors to undergo premature terminal differentiation.
Published 2025“…At 14dpa, a time when ectopic eyes began to emerge, <i>map3k1(RNAi)</i> worms showed a decrease in <i>ovo</i><sup><i>+</i></sup> eye progenitors. …”
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819
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820