Table 2.
CNN: Cartesian | CNN: Polar-min | CNN: Polar-max | |
---|---|---|---|
Architecture | ResNet-34 | ResNet-34 | ResNet-34 |
Parameters | 21.3 M | 21.3 M | 21.3 M |
Dropout | 0.5 | 0.5 | 0.5 |
Image size | 64 – > 512 | 64 – > 512 | 64 – > 512 |
Batch size | 16 | 8 | 8 |
Validation loss | 0.15024 | 0.1616 | 0.1639 |
Early stopping after | 12 epochs | 12 epochs | 12 epochs |
Learning rate (last layers) | 0.008272 | 0.008642 | 0.006792 |
Learning rates (all layers) | [0.001034, 0.002068, 0.004136, 0.008272] | [0.00108, 0.00216, 0.004321, 0.008642] | [0.000849, 0.001698, 0.003396, 0.006792] |
Epochs | 700 | 550 | 650 |