Comparative experimental results. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Algorithm operation steps. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

SCI-YOLO11. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Dataset for insulator defect detection. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

YOLOV8. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Faster-RCNN. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Results of ablation experiments. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Structure diagram of SPDConv. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Wise-IOU regression diagram. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Visualization of detection results. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Structure diagram of the SE attention mechanism. by Junyan Wang (4738518)

“…However, small object detection faces numerous challenges, such as significant difficulty, substantial interference from complex backgrounds, and inconsistent annotation quality. …”

Prevalence of low semen quality including 95% confidence interval (CI) for medication at the ATC 3 level. by P.G.J. ter Horst (21743830)

Subjects:

S1 Data - Medication, age and abstinence days associated with low semen quality: A cross-sectional study in more than 7000 men visiting the centre for reproductive medicine by P.G.J. ter Horst (21743830)

Subjects:

Univariable and multivariable analyses (age-adjusted), concerning a selection of medicaments p < 0.1 and n ≥ 10. by P.G.J. ter Horst (21743830)

Subjects:

Prevalence of low semen quality including 95% confidence interval (CI) for medication at the ATC 7 level. by P.G.J. ter Horst (21743830)

Subjects:

Univariable and multivariable analyses (age- and abstinence days-adjusted), concerning medicament(s) use and Low Semen Quality (LSQ). by P.G.J. ter Horst (21743830)

Subjects:

A. Proportion of men with Low Semen Quality (LSQ) including 95% confidence interval (CI) versus prevalence, overall and for men on medication(s) (M); B: Point estimates with 95% CI... by P.G.J. ter Horst (21743830)

Subjects:

Prevalence of low semen quality including 95% confidence interval (CI) for medication at the ATC 5 level. by P.G.J. ter Horst (21743830)

Subjects:

Univariable and multivariable analyses (age- and abstinence days-adjusted), concerning a selection of medicaments with n ≥ 10 medicament users and p < 0.1 by univariate analysis.... by P.G.J. ter Horst (21743830)

Subjects:

Top 10 significant functional annotations of up-regulated DEGs. by Meitner Cadena (22216261)

“…Functional annotations are ordered by decreasing significance, with color indicating significance according to the legend’s color scale, the ratio of genes on the horizontal axis, and DEG count represented by circle size.…”