Table 5 Experiments configuration of CapsNet
From: Deep convolutional neural network based medical image classification for disease diagnosis
| Â | Configuration |
|---|---|
Test1 | Aug0 |
Test2 | Aug1 |
Test3 | Aug1 with 64 feature maps and 64 input size |
Test4 | Aug1 with 64 feature maps and 128 input size |
Test5 | Aug1 with 32 feature maps and 64 input size |
Test6 | Aug1 with 32 feature maps and 128 input size |
Test7 | Aug1 with 32 feature maps and 48 input size |
Test8 | Aug1 with 24 feature maps and 64 input size |
Test9 | Aug1 with 16 feature maps and 64 input size |
Test10 | Aug1 with 32 feature maps, 64 input size and half primary capsule (4) |
Test11 | Aug1 with 32 feature maps, 64 input size, half primary capsule (4) and half capsule channel (16) |
Test12 | Aug1 with 32 feature maps, 64 input size, half primary capsule (4) and one fourth capsule channel (8) |
Test13 | Aug1 with 24 feature maps, 64 input size, half primary capsule (4) and half capsule channel (16) |
Test14 | Aug1 with 32 feature maps, 64 input size, half primary capsule (4) and half capsule channel (16) with more image by augmentation (10,000) |