Search alternatives:
robust optimization » process optimization (Expand Search), robust estimation (Expand Search), joint optimization (Expand Search)
whale optimization » swarm optimization (Expand Search)
primary data » primary care (Expand Search)
binary most » binary mask (Expand Search)
data whale » data where (Expand Search), data wales (Expand Search)
robust optimization » process optimization (Expand Search), robust estimation (Expand Search), joint optimization (Expand Search)
whale optimization » swarm optimization (Expand Search)
primary data » primary care (Expand Search)
binary most » binary mask (Expand Search)
data whale » data where (Expand Search), data wales (Expand Search)
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Proposed model tuned hyperparameters.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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The workflow of the proposed model.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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ResNeXt101 training and results.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Proposed model specificity and DSC outcomes.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Accuracy comparison of proposed and other models.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Architecture of ConvNet.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Comparison of state-of-the-art method.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Proposed model sensitivity outcome.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Proposed ResNeXt101 operational flow.
Published 2024“…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …”
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Predicting Thermal Decomposition Temperature of Binary Imidazolium Ionic Liquid Mixtures from Molecular Structures
Published 2021“…The subset of optimal descriptors was screened by combining the genetic algorithm with the multiple linear regression method. …”
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Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data
Published 2021“…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …”
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…<br>The consistency of the results across different kernels demonstrates that the information contained in the habitat, by itself, leads to a very simple optimal decision rule (mostly the prediction of the most frequent class per habitat), which cannot be improved solely by model adjustments. …”
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DataSheet_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Despite the increased complexity associated with binary classification, it remained more efficient, offering higher classification accuracy for samples and facilitating the selection of the most relevant time or variables, such as cooking time ≤ 30 minutes. …”
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Table_1_Near infrared spectroscopy for cooking time classification of cassava genotypes.docx
Published 2024“…Despite the increased complexity associated with binary classification, it remained more efficient, offering higher classification accuracy for samples and facilitating the selection of the most relevant time or variables, such as cooking time ≤ 30 minutes. …”