Algorithm training accuracy experiments. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Repeat the detection experiment. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Detection network structure with IRAU [34]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Ablation experiments of various block. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

Kappa coefficients for different algorithms. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of ASPP+ block. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of attention gate block [31]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

DSC block and its application network structure. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of multi-scale residual block [30]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

The structure of IRAU and Res2Net+ block [22]. by Yingying Liu (360782)

“…The actual accuracy and mean latency time of the model were 92.43% and 260ms, respectively. …”

DoLP characterization of clustering results. by Dolores Bernenko (16528426)

Identification of Key Genes. by Chen Wang (88408)

Boxplots showing the differences in miR-21-5p and miR-16-5p levels across increasing AKI severity based on Kidney Disease: Improving Global Outcomes (KDIGO) grades. by Tamar J. van der Aart (22184206)

Characteristics of children in the study. by Shijie Yu (511369)

“…<div><p>Background:</p><p>Previous study on the relationship between myopia and health-related quality of life (HRQOL) among children was only conducted within hospital setting, and this relationship in school environment remained unknown. …”

Effect size distribution and intersections of transcript usage response upon stimulation with <i>M</i>. <i>leprae</i> sonicate by T1R-free (LEP) and T1R-destined (T1R) leprosy pati... by Wilian Correa-Macedo (11813183)

“…The bar chart on the bottom left indicates the total number of increased (over) or decreased (under) transcript usage by the two groups, while the bottom panel identifies how sets intersected. …”

Relationships between clay and quartz content, TOC, 2D-NMR solid OM, S₁, 2D-NMR light oil and fractal dimensions. by Changjun Ji (18285907)

Generated spline library. by Zhe Hu (787283)

“…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”

Correlation coefficient matrix. by Zhe Hu (787283)

“…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”

Actual measurement of shape errors. by Zhe Hu (787283)

“…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”

RMSE versus learning rate. by Zhe Hu (787283)

“…Then, the LSTM model is trained using this sliding window approach, achieving a root mean square error(RMSE) of 0.03 on the test set. …”