Table 2.

The classification results of validation and test sets.

Models	Validation				Unseen Test
	Loss	Accuracy	Precision	Recall	Accuracy	Precision	F1 score	Cohen’s Kappa	MCC
DenseNet121	0.0223	0.994	0.994	0.993	0.780	0.798	0.780	0.775	0.776
DenseNet201	0.0202	0.995	0.995	0.994	0.785	0.809	0.788	0.731	0.735
Xception	0.0290	0.990	0.992	0.989	0.770	0.791	0.769	0.712	0.717
ResNet50	0.0340	0.990	0.992	0.988	0.790	0.795	0.784	0.737	0.740
DaViT_T	0.0108	0.996	0.996	0.996	0.840	0.846	0.840	0.800	0.801
CotNetSE152D	0.0166	0.993	0.993	0.993	0.835	0.852	0.833	0.793	0.798
IFormerBase	0.0096	0.996	0.997	0.996	0.860	0.874	0.861	0.825	0.827
TinyViT_21M	0.0331	0.994	0.995	0.992	0.830	0.848	0.833	0.787	0.790