Table 4 Training loss with varying numbers of convolutional layer and augmentation, presented using the common logarithm.
From: Exploring potential of Turing pattern classification through convolution maps
| Â | L1 | L1-Aug | L2 | L2-Aug | L3 | L3-Aug |
|---|---|---|---|---|---|---|
min | \(-4.207\) | \(-4.101\) | \(-4.761\) | \(-4.741\) | \(-5.008\) | \(-5.080\) |
max | \(-4.174\) | \(-3.999\) | \(-4.471\) | \(-3.028\) | \(-3.030\) | \(-3.028\) |
