Table 14 Training parameters for the HVU-E classifier.
From: A novel hybrid vision UNet architecture for brain tumor segmentation and classification
Parameters | Value |
|---|---|
Input Size | 256\(\times\)256\(\times\)3 |
Convolution Kernel size | 3\(\times\)3 |
Max pool size | 2\(\times\)2 |
Stride | 2 |
Learning rate | 0.001 |
No. of epochs | 50 |
Batch size | 32 |
Optimizer | Adam |
Activation Function | Softmax |
Loss | Categorical cross-entropy |
