بدائل البحث:
based optimization » whale optimization (توسيع البحث)
while optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), phase optimization (توسيع البحث)
binary b » binary _ (توسيع البحث)
b while » b whole (توسيع البحث), a while (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
while optimization » whale optimization (توسيع البحث), wolf optimization (توسيع البحث), phase optimization (توسيع البحث)
binary b » binary _ (توسيع البحث)
b while » b whole (توسيع البحث), a while (توسيع البحث)
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Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf
منشور في 2024"…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"
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Comparison analysis of computation time.
منشور في 2024"…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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Process flow diagram of CBFD.
منشور في 2024"…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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Precision recall curve.
منشور في 2024"…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"
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Supplementary file 1_Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery.docx
منشور في 2025"…</p>Methods<p>Thirteen supervised classification algorithms were comparatively evaluated, encompassing traditional spectral/statistical classifiers—Maximum Likelihood, Mahalanobis Distance, Minimum Distance, Parallelepiped, Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), and Binary Encoding—and machine learning algorithms including Decision Tree (DT), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Network (ANN). …"
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DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
منشور في 2024"…Utilizing the binary “One-vs-Rest” strategy, the model based on the RadImageNet dataset demonstrated superior efficacy in predicting Class 0, achieving an AUC of 0.969 and accuracy of 0.863. …"
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Flow diagram of the automatic animal detection and background reconstruction.
منشور في 2020"…(E) The threshold value is calculated based on the histogram: it is the mean of the image subtracted by 4 (optimal value defined by trial and error). …"
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PathOlOgics_RBCs Python Scripts.zip
منشور في 2023"…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …"
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Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx
منشور في 2025"…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …"
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Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield...
منشور في 2022"…Finally, we implemented and compared the different feature selection algorithms to integrate the structural features, brain networks, and voxel features to optimize the diagnostic identifications of AD using support vector machine (SVM) classifiers. …"