The relevant data file for this article. by Linsha Liu (20378293)

Line fringe structured light generation process. by Guofeng Qin (11025170)

Goal relevance. by Maeva El Bouchikhi (20442436)

“…They highlighted an important number of ethical issues which could be grouped into five overarching categories: goal relevance, adverse side effects, role of employees, data process, and vagueness. …”

Data process. by Maeva El Bouchikhi (20442436)

“…They highlighted an important number of ethical issues which could be grouped into five overarching categories: goal relevance, adverse side effects, role of employees, data process, and vagueness. …”

Relevant computed image data. by Zhaoyu Ku (20660546)

Face detection process based on AdaBoost algorithm. by Yingying Mei (13817440)

Flowchart of LFAM for feature fusion. by Dinghong Mu (14204200)

Subjects: “…proposed optimization algorithm…”

The model parameters of SIFusion and comparative algorithms. by Song Qian (5031221)

Summary of relevant works. by Bashir Olaniyi Sadiq (22478011)

PRISMA flowchart for the study selection process. by Yong Lin Lai (20854961)

Subjects: “…underlying degradation processes…”

Evaluation parameter performance of each algorithm (In six light scenes). by Chao Ma (207385)

Subjects:

The relevant code in the manuscript can be found in the supporting information data file. by Xini Fang (20861990)

Schematic of Learnable weights fusion module. by Yazhou Li (277980)

“…Additionally, the model introduces a learnable weighted feature fusion module in the neck, which enhances the expression of features at multiple scales and different levels, thus improving the focus on key features. …”

Model-relevant variable data for external patients. by Lei Gao (6566)

Illustration of the recursive objective space exploration process implemented by the ROSE algorithm. by Ihab Hashem (21156806)

Subjects:

Algorithm for optimizing the model using transformer. by Weiling Liu (1465480)

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

“…The results show: (1) Random oversampling, ADASYN, SMOTE, and SMOTEENN were used for data balance processing, among which SMOTEENN showed better efficiency and effect in dealing with data imbalance. (2) The GA-XGBoost model optimized the hyperparameters of the XGBoost model through a genetic algorithm to improve the model’s predictive accuracy. …”

Relevant data underlying the findings described in manuscript. by Lin Qi (128224)

Data generation algorithm. by Aluwani Ramalata (21262977)

The AP for different detection algorithms on the RSOD dataset. by Guoguang Hua (22305400)