Search alternatives:
marked decrease » marked increase (Expand Search)
set generation » next generation (Expand Search), heat generation (Expand Search), situ generation (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
marked decrease » marked increase (Expand Search)
set generation » next generation (Expand Search), heat generation (Expand Search), situ generation (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
-
1
-
2
-
3
-
4
-
5
-
6
-
7
-
8
-
9
-
10
-
11
-
12
-
13
-
14
-
15
-
16
-
17
-
18
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. …”
-
19
-
20
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. …”