Area under the ROC curve (AUC) analysis to predict neurological severity at 6-months and 1-year following acute cervical tSCI. by Harshit Arora (22008280)

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Spearman correlations between the various baseline radiological parameters. by Harshit Arora (22008280)

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Follow-up for individuals with acute cervical tSCI (n = 103). by Harshit Arora (22008280)

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STROBE Flow Diagram Describing Study Cohort Selection. by Harshit Arora (22008280)

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Artwork demonstrating the principal tSCI compression subtypes. by Harshit Arora (22008280)

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Baseline demographic and clinical characteristics of individuals admitted with cervical tSCIs (n = 169). by Harshit Arora (22008280)

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Summary of previous work. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Comparison of MAP@0.5 results from experiments. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

YOLO11. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Structure of the SCI-YOLO11 network. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Comparative experimental results. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Algorithm operation steps. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

SCI-YOLO11. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

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

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

YOLOV8. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Faster-RCNN. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Results of ablation experiments. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Structure diagram of SPDConv. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

Visualization of detection results. by Junyan Wang (4738518)

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”

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

“…In response to the adverse effects caused by inconsistent annotation quality on defect image detection performance, we incorporate Wise-IoU-V3 loss function to optimize boundary box regression performance effectively mitigating negative impacts stemming from uneven annotation quality. …”