Table 1 The setting of parameters for the developed network.

From: DTASUnet: a local and global dual transformer with the attention supervision U-network for brain tumor segmentation

Type of hyper-parameter

Value

Epoch

300

Batch size

1

Initial learning rate

1e − 4

Learning rate decay strategy

Cosine annealing

Optimizer

Adam

Loss function

Dice loss

Supervisory loss weights

0.7

Cross-validation split

0.2

Patch embedding dim

48

Window size

7