Search alternatives:
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
yet optimization » art optimization (Expand Search), lead optimization (Expand Search), path optimization (Expand Search)
image learning » maze learning (Expand Search), face learning (Expand Search), aware learning (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
yet optimization » art optimization (Expand Search), lead optimization (Expand Search), path optimization (Expand Search)
image learning » maze learning (Expand Search), face learning (Expand Search), aware learning (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
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Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm
Published 2025“…Our results show that deep learning and optimization </p><p dir="ltr">methods, such as the binary GWO algorithm, can be successfully applied to melanoma diagnosis. …”
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ROC curve for binary classification.
Published 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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Confusion matrix for binary classification.
Published 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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The flowchart of the proposed algorithm.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
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A* Path-Finding Algorithm to Determine Cell Connections
Published 2025“…The integration of heuristic optimization and machine learning significantly enhances both speed and precision in astrocyte data analysis. …”
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The statistical description of the original data set of the patients (<i>n</i> = 162).
Published 2025Subjects: -
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The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
Published 2025Subjects: -
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Data_Sheet_1_Pneumonia detection by binary classification: classical, quantum, and hybrid approaches for support vector machine (SVM).pdf
Published 2024“…Our aim is to develop a machine learning tool that can accurately classify images as belonging to normal or infected individuals. …”
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ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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The comparison of the accuracy score of the benchmark and the proposed models.
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Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
Published 2025Subjects: