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61
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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62
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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63
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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64
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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65
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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66
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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67
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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68
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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69
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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70
Participants demographic data.
Published 2025“…A decrease in mean erector spinae activity was observed in males only. …”
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74
Modulation of sound responsiveness during repetitive stress.
Published 2025“…<p>(a) Percentage of sound-responsive cells in baseline and repeated stress conditions for PPy and PV cells (all imaged cells). There was a small and significant decrease in the percentage of responsive PPy cells (<i>n</i> = 10 sessions in baseline and 15 sessions during stress, <i>t</i> test, <i>p</i> = 0.02) and a nonsignificant decrease for PV cells (mean ± SE, <i>n</i> = 190 cells in baseline and 339 cells during stress, <i>t</i> test, <i>p</i> = 0.19). …”
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75
Supporting data for PhD thesis "Turbulence in Thermally-Stratified Boundary Layers over Idealized Urban Morphology"
Published 2024“…Large-scale accelerating flows in the UCL enhance small-scale turbulence, showing a monotonic decrease in AM with increasing instability. …”
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76
Analyses of directed phase lag index (dPLI [44]) for excitatory/inhibitory (E/I) ratios with respect to pyramidal (Pyr) and parvalbumin (PV) populations (<i>A</i>) and Pyr and soma...
Published 2025“…However, in contrast to the E/I ratio for the PV population, increasing the E/I ratio by decreasing SOM interneuron numbers tended to decrease the dPLI values from PV to Pyr populations. …”
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77
Supplementary file 1_Effects of a personalized PERMA-based intervention on the mental health of junior high school students: a randomized clinical trial.docx
Published 2025“…The experimental group also demonstrated significant increases in accomplishment (+1.4), engagement (+1.2), goal focus (+2.1), positive cognition (+1.5), and total resilience (+5.2). …”
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78
Ama controls the pool of myoblast number independently of Nrt.
Published 2024“…Note that overexpressing <i>Ama</i> (Ama OE) is not sufficient to induce an increase of myoblast number. <b>(L)</b> Dot-plot graph showing the mean number of Twi-positive myoblasts per disc in rescue experiments using R32D05-Gal4 driver. …”
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79
Data Sheet 1_Treatment with pemafibrate ameliorates fatty liver index and atherogenic lipid profiles in Japanese patients with type 2 diabetes mellitus.pdf
Published 2025“…</p>Results<p>Treatment with pemafibrate significantly increased mean levels of high-density lipoprotein cholesterol (HDL-C) (baseline/3M/6M/12M: 46/55/55/54 mg/dL) and decreased median levels of triglycerides (baseline/3M/6M/12M: 211/112/99/98 mg/dL), non-HDL-C (146/128/125/121 mg/dL), small dense low-density lipoprotein cholesterol (45/33/30/30 mg/dL) and remnant-like particle cholesterol (8.1/2.6/2.3/2.4 mg/dL). …”
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80
Table 1_Effect of a mindfulness-based cognitive behavior therapy intervention on occupational burnout among school teachers.docx
Published 2025“…No significant differences between the arms were found in the post-test mean levels of EE, DP, and PA. …”