Search alternatives:
models optimization » model optimization (Expand Search), process optimization (Expand Search), codon optimization (Expand Search)
based optimization » whale optimization (Expand Search), bayesian optimization (Expand Search)
binary art » binary pairs (Expand Search)
models optimization » model optimization (Expand Search), process optimization (Expand Search), codon optimization (Expand Search)
based optimization » whale optimization (Expand Search), bayesian optimization (Expand Search)
binary art » binary pairs (Expand Search)
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The comparison of the accuracy score of the benchmark and the proposed models.
Published 2025Subjects: -
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Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…Pixel paths were classified using a z-score brightness threshold of 1.21, optimized for noise reduction and accuracy. The A* algorithm then evaluated connectivity by minimizing Euclidean distance and heuristic cost between cells. …”
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Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
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The statistical description of the original data set of the patients (<i>n</i> = 162).
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The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…The goal of this </p><p dir="ltr">research is to combine state-of-the-art deep learning techniques with optimization algorithms to develop a precise </p><p dir="ltr">and efficient predictive system for melanoma detection. …”
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Dataset 1: Zip file containing the figures of the presented methods and results in jpeg files
Published 2025“…<p dir="ltr">Figures represented here illustrates the <b>metaheuristic-based band selection framework</b> for hyperspectral image classification using <b>Binary Jaya Algorithm enhanced with a mutation operator</b> to improve population diversity and avoid premature convergence. …”
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Classification baseline performance.
Published 2025“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”
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Feature selection results.
Published 2025“…The contributions include developing a baseline Convolutional Neural Network (CNN) that achieves an initial accuracy of 86.29%, surpassing existing state-of-the-art deep learning models. Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”