Table 2.

Parameter settings for the four stages of the ViT-DFG framework, including preprocessing, deep feature generation, INCA-based feature selection, and classification

Stages	Process/function	Parameters
	Resizing	224 $\times$ 224
Preprocessing	Hold-out validation	70% train, 15% test, 15% validation
	k-fold cross-validation	5-fold, 80% train, 20% test
	Base ViT	6 M parameters, 23 Encoder Blocks, 768 features
Deep Feature Generation	Swin	49 M parameters, 4 stages, [2, 2, 18, 2] blocks, 768 features
	MaxViT	31 M parameters, 4 Blocks, 512 features
iNCA Feature Selector	Range of iteration	[250, 1250]
	k-NN (criteria)	n_neighbors = 1
	k-NN	n_neighbors = 1
Classifier	SoftMax	Adam optimizer, ReLU and softmax activation function, epoch = 40, batch size = 32, learning rate = 1e-4