Table 3.
Performance results for different CNN model configurations, using random cross validation executed 5 times (we report the mean and standard deviation of all executions). Configuration parameters: K1, size of the convolutional filter; K2, size of the subsampling mask; K3, number of fully connected layers; K4, number of neurons in fully connected layers; K5, number of epochs; K6, size of the minibatch.
| Configuration ID | K1 | K2 | K3 | K4 | K5 | K6 | Test accuracy (%) | Number of parameters | Training time (s) |
|---|---|---|---|---|---|---|---|---|---|
| (1) | 600 | 4 | 1 | 20 | 100 | 40 | 98.43 (σ = 0.88) | 2968 | 16.38 (σ = 1.08) |
| (2) | 400 | 4 | 1 | 20 | 100 | 40 | 98.43 (σ = 1.47) | 3368 | 21.48 (σ = 0.54) |
| (3) | 750 | 4 | 1 | 20 | 100 | 40 | 98.04 (σ = 1.75) | 2658 | 7.65 (σ = 0.17) |
| (4) | 600 | 2 | 1 | 20 | 100 | 40 | 98.04 (σ = 2.15) | 3968 | 15.61 (σ = 0.46) |
| (5) | 600 | 11 | 1 | 20 | 100 | 40 | 97.25 (σ = 2.00) | 2328 | 17.67 (σ = 0.45) |
| (6) | 600 | 4 | 2 | 22 | 100 | 40 | 98.43 (σ = 1.92) | 3590 | 16.43 (σ = 0.45) |
| (7) | 600 | 4 | 3 | 10 | 100 | 40 | 96.86 (σ = 2.66) | 2608 | 15.60 (σ = 0.40) |
| (8) | 600 | 4 | 1 | 10 | 100 | 40 | 96.08 (σ = 5.95) | 2388 | 15.31 (σ = 0.70) |
| (9) | 600 | 4 | 1 | 32 | 100 | 40 | 97.65 (σ = 2.88) | 3664 | 15.93 (σ = 0.35) |
| (10) | 600 | 4 | 1 | 20 | 80 | 40 | 98.04 (σ = 1.24) | 2968 | 12.97 (σ = 0.81) |
| (11) | 600 | 4 | 1 | 20 | 120 | 40 | 98.43 (σ = 0.78) | 2968 | 18.28 (σ = 0.40) |
| (12) | 600 | 4 | 1 | 20 | 100 | 35 | 98.04 (σ = 1.24) | 2968 | 17.19 (σ = 0.47) |
| (13) | 600 | 4 | 1 | 20 | 100 | 60 | 96.86 (σ = 2.00) | 2968 | 14.83 (σ = 0.53) |