Table 2 Classification results on the original pmg dataset.

Dataset	Metric	ResNet-50	ResNet-101	VGG-16	MobileNetV2	DenseNet-201
Training	Accuracy	0.815	0.747	0.938	0.997	0.998
	Loss	0.490	0.554	0.285	0.114	0.080
	Precision	0.836	0.761	0.934	0.998	0.998
	Recall	0.788	0.726	0.943	0.996	0.998
	F1 Score	0.751	0.683	0.929	0.989	0.992
	Cohen’s Kappa	0.603	0.422	0.904	0.994	0.998
Validation	Accuracy	0.765	0.753	0.950	0.993	0.995
	Loss	0.513	0.543	0.272	0.120	0.081
	Precision	0.697	0.789	0.938	0.990	0.991
	Recall	0.929	0.684	0.962	0.997	0.998
	F1 Score	0.783	0.712	0.950	0.976	0.996
	Cohen’s Kappa	0.614	0.423	0.899	0.980	0.992
Test	Accuracy	0.836	0.751	0.951	0.988	0.996
	Loss	0.484	0.551	0.277	0.128	0.080
	Precision	0.876	0.789	0.944	0.992	0.993
	Recall	0.779	0.677	0.957	0.985	0.998
	F1 Score	0.793	0.708	0.949	0.991	0.993
	Cohen’s Kappa	0.640	0.470	0.897	0.983	0.987

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