Search alternatives:
policy optimization » topology optimization (Expand Search), wolf optimization (Expand Search), process optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
image model » damage model (Expand Search), primate model (Expand Search), climate model (Expand Search)
binary base » binary mask (Expand Search), ciliary base (Expand Search)
base policy » leave policy (Expand Search)
policy optimization » topology optimization (Expand Search), wolf optimization (Expand Search), process optimization (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
image model » damage model (Expand Search), primate model (Expand Search), climate model (Expand Search)
binary base » binary mask (Expand Search), ciliary base (Expand Search)
base policy » leave policy (Expand Search)
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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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Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment
Published 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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Summary of existing CNN models.
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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Testing results for classifying AD, MCI and NC.
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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