بدائل البحث:
based optimization » whale optimization (توسيع البحث)
dose optimization » model optimization (توسيع البحث), wolf optimization (توسيع البحث), design optimization (توسيع البحث)
binary ct » binary _ (توسيع البحث)
binary b » binary _ (توسيع البحث)
ct based » _ based (توسيع البحث)
b dose » b doses (توسيع البحث), _ dose (توسيع البحث), a dose (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
dose optimization » model optimization (توسيع البحث), wolf optimization (توسيع البحث), design optimization (توسيع البحث)
binary ct » binary _ (توسيع البحث)
binary b » binary _ (توسيع البحث)
ct based » _ based (توسيع البحث)
b dose » b doses (توسيع البحث), _ dose (توسيع البحث), a dose (توسيع البحث)
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Steps in the extraction of 14 coordinates from the CT slices for the curved MPR.
منشور في 2025"…Protruding paths are then eliminated using graph-based optimization algorithms, as demonstrated in f). …"
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3
DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). Two NIRs devices, the portable QualitySpec® Trek (QST) and the benchtop NIRFlex N-500 were used to collect spectral data. …"
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Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
منشور في 2024"…Cooking data were classified into binary and multiclass variables (CT4C and CT6C). Two NIRs devices, the portable QualitySpec® Trek (QST) and the benchtop NIRFlex N-500 were used to collect spectral data. …"
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DataSheet_1_Exploring deep learning radiomics for classifying osteoporotic vertebral fractures in X-ray images.docx
منشور في 2024"…Logistic regression emerged as the optimal machine learning algorithm for both DLR models. …"
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6
Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles
منشور في 2025"…</p><p dir="ltr">Encoding: Categorical variables such as surface coating and cell type were grouped into logical classes and label-encoded to enable model compatibility.</p><p dir="ltr"><b>Applications and Model Compatibility:</b></p><p dir="ltr">The dataset is optimized for use in supervised learning workflows and has been tested with algorithms such as:</p><p dir="ltr">Gradient Boosting Machines (GBM),</p><p dir="ltr">Support Vector Machines (SVM-RBF),</p><p dir="ltr">Random Forests, and</p><p dir="ltr">Principal Component Analysis (PCA) for feature reduction.…"