Search alternatives:
significantly increased » significant increase (Expand Search)
increased decrease » increased release (Expand Search), increased crash (Expand Search)
time decrease » time increased (Expand Search), sizes decrease (Expand Search), we decrease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
significantly increased » significant increase (Expand Search)
increased decrease » increased release (Expand Search), increased crash (Expand Search)
time decrease » time increased (Expand Search), sizes decrease (Expand Search), we decrease (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
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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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2774
MIT-BIH dataset proportion analysis chart.
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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2775
Wavelet transform preprocessing results.
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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2776
PCAECG_GAN.
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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2777
MIT dataset expansion quantities and Proportions.
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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2778
Experimental hardware and software environment.
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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2779
PCA-CGAN K-fold experiment table.
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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2780
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. …”