PCA-CGAN Structure Diagram. by Chao Tang (10925)

“…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. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

Comparison of Model Five-classification Results. by Chao Tang (10925)

“…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. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCAECG-GAN K-fold experiment table. by Chao Tang (10925)

“…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. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Pseudocode Table. by Chao Tang (10925)

“…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. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

PCA-CGAN Ablation Experiment Results. by Chao Tang (10925)

“…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. After data augmentation, the ResNet model’s average F1 score improved significantly, with particularly outstanding performance on rare categories such as atrial premature beats, far surpassing traditional methods like SigCWGAN and TD-GAN. …”

The speed diagram. by Yifei Li (198040)

Subjects:

Factors of orthogonal experiment. by Yifei Li (198040)

Subjects:

Analysis of variance in orthogonal test. by Yifei Li (198040)

Subjects:

Comparison between simulation tests and bench tests. by Yifei Li (198040)

Subjects:

Schematic diagram of the millet characteristic dimensions. by Yifei Li (198040)

Subjects:

Structure and collision diagram of the millet hole seeding system. by Yifei Li (198040)

Subjects:

Analysis of variance in orthogonal test. by Yifei Li (198040)

Subjects:

Comparison between simulation tests and bench tests. by Yifei Li (198040)

Subjects:

Comparison between simulation tests and bench tests. by Yifei Li (198040)

Subjects:

Effect of collision variety on COR. by Yifei Li (198040)

Subjects:

Appearance parameters of the millet in Heilongjiang. by Yifei Li (198040)

Subjects:

Scheme and results of orthogonal test. by Yifei Li (198040)

Subjects:

Effect of collision material on COR. by Yifei Li (198040)

Subjects:

Effect of collision speed on COR. by Yifei Li (198040)

Subjects:

Computational parameters used in the simulations. by Yifei Li (198040)

Subjects: