بدائل البحث:
resource optimization » resource utilization (توسيع البحث), resource utilisation (توسيع البحث), resource limitations (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
time resource » situ resource (توسيع البحث), firm resource (توسيع البحث), optimize resource (توسيع البحث)
image model » damage model (توسيع البحث), primate model (توسيع البحث), climate model (توسيع البحث)
resource optimization » resource utilization (توسيع البحث), resource utilisation (توسيع البحث), resource limitations (توسيع البحث)
model optimization » codon optimization (توسيع البحث), global optimization (توسيع البحث), based optimization (توسيع البحث)
time resource » situ resource (توسيع البحث), firm resource (توسيع البحث), optimize resource (توسيع البحث)
image model » damage model (توسيع البحث), primate model (توسيع البحث), climate model (توسيع البحث)
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CDF of task latency, approximated as the inverse of the achieved computation rate.
منشور في 2025الموضوعات: -
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Summary of existing CNN models.
منشور في 2024"…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …"
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Dynamic resource allocation process.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf
منشور في 2024"…A support vector machine (SVM) is attractive because binary classification can be represented as an optimization problem, in particular as a Quadratic Unconstrained Binary Optimization (QUBO) model, which, in turn, maps naturally to an Ising model, thereby making annealing—classical, quantum, and hybrid—an attractive approach to explore. …"
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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
منشور في 2019"…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …"
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Testing results for classifying AD, MCI and NC.
منشور في 2024"…To achieve this, we focused the study on addressing the challenge of image noise, which impacts the performance of deep learning models. …"
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Flowchart scheme of the ML-based model.
منشور في 2024"…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"
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Confusion matrix.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Parameter settings.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Event-driven data flow processing.
منشور في 2025"…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …"
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Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity
منشور في 2019"…Adopting metagenomic analysis for clinical use requires that all aspects of the workflow are optimized and tested, including data analysis and computational time and resources. …"
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Generalized Tensor Decomposition With Features on Multiple Modes
منشور في 2021"…An efficient alternating optimization algorithm with provable spectral initialization is further developed. …"
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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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DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx
منشور في 2021"…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"