From: Deep convolutional neural network based medical image classification for disease diagnosis
Sr. no | Configuration | CapsNet |
---|---|---|
1 | Aug0 | 0.748 |
2 | Aug1 | 0.788 |
3 | Aug1 with 64 feature maps and 64 input size | 0.737 |
4 | Aug1 with 64 feature maps and 128 input size | 0.627 |
5 | Aug1 with 32 feature maps and 64 input size | 0.798 |
6 | Aug1 with 32 feature maps and 128 input size | 0.784 |
7 | Aug1 with 32 feature maps and 48 input size | 0.756 |
8 | Aug1 with 24 feature maps and 64 input size | 0.798 |
9 | Aug1 with 16 feature maps and 64 input size | 0.765 |
10 | Aug1 with 32 feature maps, 64 input size and half primary capsule (4) | 0.811 |
11 | Aug1 with 32 feature maps, 64 input size, half primary capsule (4) and half capsule channel (16) | 0.825 |
12 | Aug1 with 32 feature maps, 64 input size, half primary capsule (4) and one fourth capsule channel (8) | 0.752 |
13 | Aug1 with 24 feature maps, 64 input size, half primary capsule (4) and half capsule channel (16) | 0.825 |
14 | Aug1 with 32 feature maps, 64 input size, half primary capsule (4) and half capsule channel (16) with more image by augmentation (10,000) | 0.788 |