Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
basic process » based process (Expand Search), basic protein (Expand Search)
primary role » primary care (Expand Search), primary goal (Expand Search)
binary basic » binary mask (Expand Search)
role model » role models (Expand Search), one model (Expand Search), rate model (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), based optimization (Expand Search)
basic process » based process (Expand Search), basic protein (Expand Search)
primary role » primary care (Expand Search), primary goal (Expand Search)
binary basic » binary mask (Expand Search)
role model » role models (Expand Search), one model (Expand Search), rate model (Expand Search)
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Internal architecture of the SPAM-XAI model.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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SPAM-XAI compared with previous models.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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Overview of SPAM-XAI model complete architecture.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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DEM error verified by airborne data.
Published 2024“…<div><p>The accuracy of digital elevation models (DEMs) in forested areas plays a crucial role in canopy height monitoring and ecological sensitivity analysis. …”
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Error of ICESat-2 with respect to airborne data.
Published 2024“…<div><p>The accuracy of digital elevation models (DEMs) in forested areas plays a crucial role in canopy height monitoring and ecological sensitivity analysis. …”
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Data used in this study.
Published 2024“…<div><p>The accuracy of digital elevation models (DEMs) in forested areas plays a crucial role in canopy height monitoring and ecological sensitivity analysis. …”
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Transect in parts of California.
Published 2024“…<div><p>The accuracy of digital elevation models (DEMs) in forested areas plays a crucial role in canopy height monitoring and ecological sensitivity analysis. …”
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SPAM-XAI confusion matrix.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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Illustration of MLP.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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Dataset detail division.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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Software defects types.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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SMOTE representation.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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35
Demonstration confusion matrix.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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Analysis PC2 AU-ROC curve.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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PROMISE defects prediction attribute aspects.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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SPAM-XAI confusion matrix using PC2 dataset.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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SPAM-XAI using the PC1 dataset.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”
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SPAM-XAI using the CM1 dataset.
Published 2024“…The SPAM-XAI model reduces features, optimizes the model, and reduces time and space complexity, enhancing its robustness. …”