Table 3 Effect of CNN architecture on classification accuracy (cols. 2,3) and number of parameters per layer (cols. 4-9) in each architecture
From: DeepSort: deep convolutional networks for sorting haploid maize seeds
Method | Train | Test | Conv1 | Conv2 | Full1 | Full2 | Output | Total |
|---|---|---|---|---|---|---|---|---|
Arch-1 | 1.000 | 0.968 | 1216 | 6416 | 786,624 | 18,528 | 194 | 812,978 |
Arch-2 | 1.000 | 0.968 | 608 | 1608 | 196,704 | 4656 | 98 | 203,674 |
Arch-3 | 0.992 | 0.941 | 304 | 404 | 49,200 | 1176 | 50 | 51,134 |
Arch-4 | 0.989 | 0.935 | 304 | - | 98,328 | - | 50 | 98,682 |