Search alternatives:
marked decrease » marked increase (Expand Search)
set decrease » step decrease (Expand Search), sizes decrease (Expand Search), mean decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
marked decrease » marked increase (Expand Search)
set decrease » step decrease (Expand Search), sizes decrease (Expand Search), mean decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
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A novel RNN architecture to improve the precision of ship trajectory predictions
Published 2025“…To solve these challenges, Recurrent Neural Network (RNN) models have been applied to STP to allow scalability for large data sets and to capture larger regions or anomalous vessels behavior. …”
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Prediction (a-d) and infusion deviation (e-f) results under different training sets and test sets.
Published 2025Subjects: -
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Classification model parameter settings.
Published 2025“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. …”
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PCA-CGAN model parameter settings.
Published 2025“…Experiments demonstrate that PCA-CGAN not only achieves stable convergence on a large-scale heterogeneous dataset comprising 43 patients for the first time but also resolves the “dilution effect” problem in data augmentation, avoiding the asymmetric phenomenon where Precision increases while Recall decreases. …”
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