بدائل البحث:
field optimization » lead optimization (توسيع البحث), guided optimization (توسيع البحث), linear optimization (توسيع البحث)
codon optimization » wolf optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
based codon » based color (توسيع البحث), based cohort (توسيع البحث), based action (توسيع البحث)
field optimization » lead optimization (توسيع البحث), guided optimization (توسيع البحث), linear optimization (توسيع البحث)
codon optimization » wolf optimization (توسيع البحث)
library based » laboratory based (توسيع البحث)
based codon » based color (توسيع البحث), based cohort (توسيع البحث), based action (توسيع البحث)
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Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX
منشور في 2021"…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …"
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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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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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Thesis-RAMIS-Figs_Slides
منشور في 2024"…Importantly, this strategy locates samples adaptively on the transition between facies which improves the performance of conventional \emph{<i>MPS</i>} algorithms. In conclusion, this work shows that preferential sampling can contribute in \emph{<i>MPS</i>} even at very small sampling regimes and, as a corollary, demonstrates that prior models (obtained form a training image) can be used effectively not only to simulate non-sensed variables of the field, but to decide where to measure next.…"
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Fortran & C++: design fractal-type optical diffractive element
منشور في 2022"…</p> <p>(3) optimize the fractal and/or grid-matrix holograms for given target diffraction images, using annealing algorithms. …"