Showing 6,901 - 6,920 results of 18,468 for search 'significantly ((((larger decrease) OR (we decrease))) OR (((mean decrease) OR (a decrease))))', query time: 0.67s Refine Results
  1. 6901

    Performance comparison of three loss functions. by Yaojun Zhang (389482)

    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%. …”
  2. 6902

    mAP0.5 Curves of various models. by Yaojun Zhang (389482)

    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%. …”
  3. 6903

    Network loss function change diagram. by Yaojun Zhang (389482)

    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%. …”
  4. 6904

    Comparative diagrams of different indicators. by Yaojun Zhang (389482)

    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%. …”
  5. 6905

    YOLOv8n structure diagram. by Yaojun Zhang (389482)

    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%. …”
  6. 6906

    Geometric model of the binocular system. by Yaojun Zhang (389482)

    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%. …”
  7. 6907

    Enhanced dataset sample images. by Yaojun Zhang (389482)

    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%. …”
  8. 6908

    GluA1 promotes opioid use by Yuan-Yuan Hou (11896051)

    Published 2025
    “…In rats with steady MSA, the protein level of GluA1 subunits of glutamate AMPA receptors (AMPARs) was significantly increased, but that of GluA2 was decreased, resulting in an increased GluA1/GluA2 ratio in central nucleus of the amygdala (CeA). …”
  9. 6909

    Test materials and test methods. by Yao Long (1604773)

    Published 2025
    “…As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. …”
  10. 6910

    Proportions of test specimens. by Yao Long (1604773)

    Published 2025
    “…As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. …”
  11. 6911

    Basic physical properties of red sandstone soil. by Yao Long (1604773)

    Published 2025
    “…As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. …”
  12. 6912

    Main performance indicators of BF. by Yao Long (1604773)

    Published 2025
    “…As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. …”
  13. 6913

    Technical parameters of cement. by Yao Long (1604773)

    Published 2025
    “…As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. …”
  14. 6914

    Particle composition of red sandstone soil. by Yao Long (1604773)

    Published 2025
    “…As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. …”
  15. 6915
  16. 6916
  17. 6917

    SEM image of C4BF6 specimen. by Yao Long (1604773)

    Published 2025
    “…As the BF content increases, the UCS and peak deviatoric stress exhibit an initial increase followed by a decrease. At the optimal BF dosage of 6‰, the UCS improved 24.48% ~ 25.40%, while the peak deviatoric stress improved 31.13% ~ 39.48%. …”
  18. 6918
  19. 6919

    <b> </b> Energy efficiency and gas volume comparison. by Ning Zuo (17295415)

    Published 2025
    “…<div><p>Biogas energy derived from recycled algal biomass grown on wastewater could provide a sustainable pathway for a renewable future. This research investigates the chemical details of cobalt-catalysed pyrolysis integrated with methanogenic archaea co-anaerobic fermentation to improve biogas and methane generation from wastewater algae. …”
  20. 6920

    Model validation of kinetic parameters. by Ning Zuo (17295415)

    Published 2025
    “…<div><p>Biogas energy derived from recycled algal biomass grown on wastewater could provide a sustainable pathway for a renewable future. This research investigates the chemical details of cobalt-catalysed pyrolysis integrated with methanogenic archaea co-anaerobic fermentation to improve biogas and methane generation from wastewater algae. …”