Optimize process data and final results by Dawei Wang (471687)

Final settings for the algorithms. by Raphael Souza de Oliveira (12647110)

Final average rankings of algorithms in PSNR, FSIM, and SSIM. by Zhenjing Xie (18196063)

One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

Final results. by Wang Chen (559614)

Evaluation of developed intrusion detection model with different heuristic algorithms. by P. M. Vijayan (17095147)

Test performance metrics for the final model. by Ramona Leenings (11167294)

Training process. by Ning Zhao (84707)

Workpiece processing information. by Guilin Yang (583364)

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. by Benjamin Gallois (10131683)

Comparison with SOTA model in number of iterations and final cost. by Zixi Wang (459102)

The ANFIS algorithm details. by Mohammadmahdi Taheri (21722285)

Two-stage object detection algorithm process. by Xutao Liu (13006965)

Parameter setting of the testing algorithm. by Zhenjing Xie (18196063)

“…The findings reveal that DBO-Otsu substantially surpasses its counterparts in image segmentation quality and processing speed. Further empirical analysis on a dataset comprising TPD cases from level 1 to 5 underscores the algorithm’s practical utility, achieving an impressive 80% accuracy in severity level identification and underscoring its potential for TPD image segmentation and recognition tasks.…”

Test result of seven algorithms. by Zhenjing Xie (18196063)

“…The findings reveal that DBO-Otsu substantially surpasses its counterparts in image segmentation quality and processing speed. Further empirical analysis on a dataset comprising TPD cases from level 1 to 5 underscores the algorithm’s practical utility, achieving an impressive 80% accuracy in severity level identification and underscoring its potential for TPD image segmentation and recognition tasks.…”

The Search process of the genetic algorithm. by Wenguang Li (6528113)

“…Firstly, the dataset was balanced using various sampling methods; secondly, a Stacking model based on GA-XGBoost (XGBoost model optimized by genetic algorithm) was constructed for the risk prediction of diabetes; finally, the interpretability of the model was deeply analyzed using Shapley values. …”

Wilcoxon test results comparing DBO with other algorithms. by Zhenjing Xie (18196063)

Image convolution calculation process. by Xutao Liu (13006965)

Description of optimal model parameters. by Libo Liu (552605)

Algorithm parameters. by Guilin Yang (583364)