Multi-scale representation of two-dimensional linear graphs. حسب Guangmei Ma (21432861)

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Improved HMAX model running process. حسب Guangmei Ma (21432861)

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RI-HMAX image processing technology. حسب Guangmei Ma (21432861)

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Calculation time for image key information processing. حسب Guangmei Ma (21432861)

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The experimental basic environmental parameters. حسب Guangmei Ma (21432861)

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Significant region segmentation. حسب Guangmei Ma (21432861)

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CNN structure. حسب Guangmei Ma (21432861)

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Comprehensive comparison of existing methods. حسب Guangmei Ma (21432861)

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Method training loss testing. حسب Guangmei Ma (21432861)

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Analysis of rotational non-deformation characterization. حسب Guangmei Ma (21432861)

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Segmentation results of physical images. حسب Guangmei Ma (21432861)

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Scale ratio change test. حسب Guangmei Ma (21432861)

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Standard model selected for research. حسب Guangmei Ma (21432861)

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Pixel ring feature expression. حسب Guangmei Ma (21432861)

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Analysis of corner extraction results. حسب Guangmei Ma (21432861)

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Feature recognition accuracy testing. حسب Guangmei Ma (21432861)

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Data_Sheet_1_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX حسب Raymond Salvador (813880)

Data_Sheet_2_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX حسب Raymond Salvador (813880)

Data_Sheet_3_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX حسب Raymond Salvador (813880)

Flowchart of this study. حسب Aref Andishgar (18155608)

"…A total of 160 variables were included in the machine learning (ML) models, and feature scaling and one-hot encoding were employed for data processing. Ten supervised ML algorithms were utilized, namely logistic regression (LR), support vector machine (SVM), random forest (RF), Gaussian naive Bayes (GNB), linear discriminant analysis (LDA), k-nearest neighbors (KNN), gradient boosting machine (GBM), extreme gradient boosting (XGB), cat boost (CAT), and light gradient boosting machine (LGBM). …"