Algorithm detection steps. by José M. Rivera-Arbeláez (12418512)

Algorithm detection performance. by Kangning Li (6069629)

“…Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

AUC scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …”

Recall scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …”

Detection of tumor spatial domain using SKNY for multiple cancer types. by Shunsuke A. Sakai (13789939)

F1-scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …”

Illustration of the wAL GHAC algorithm on a small network. by Petr Prokop (19959315)

Summary of four signal detection algorithms. by Wangyu Ye (17616256)

Model structure of the Small_obj algorithm. by Kangning Li (6069629)

“…Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

Prediction results of a trained model for detecting the location of a tumor. by Young Seo Baik (21001443)

Prediction results of a trained model for detecting the location of a tumor. by Young Seo Baik (21001443)

Performance evaluation of community detection methods on a set of LFR benchmarking networks. by Petr Prokop (19959315)

Structural diagram of the overall SCF-YOLO algorithm. by Yazhou Li (277980)

Ablation study on the improved YOLOv5 algorithm. by Kangning Li (6069629)

“…Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

Results of the bearing defect detection. by Kangning Li (6069629)

TP predictions from a trained model for tumor location detection. by Young Seo Baik (21001443)

TP predictions from a trained model for tumor location detection. by Young Seo Baik (21001443)

Two-dimensional visualization of cell clustering in the Pollen dataset before and after imputation using multiple algorithms. by Siyi Huang (8562174)

Two-dimensional visualization of cell clustering in the Petropoulos dataset before and after imputation using multiple algorithms. by Siyi Huang (8562174)

Predicted sensitivity, specificity, PPV, and NPV of the four algorithms (a, b) and algorithms combinations (c, d) under Model-3 in the primary analysis. by Jia Wei (120974)