Table 1.

Classification metrics for different combinations of models.

Feature extractor	Classifier	Accuracy	Precision	Recall	F1-score
VGG16	XGBoost	0.87	0.86	0.86	0.85
	MLP	0.82	0.82	0.80	0.81
	RF	0.81	0.81	0.80	0.80
	SVM	0.74	0.76	0.73	0.72
Inception V3	SVM	0.88	0.86	0.87	0.87
	MLP	0.79	0.79	0.79	0.78
	RF	0.78	0.78	0.79	0.78
	XGBoost	0.77	0.77	0.78	0.77
ResNet50	RF	0.76	0.75	0.75	0.74
	MLP	0.75	0.75	0.74	0.73
	SVM	0.70	0.70	0.69	0.68
	XGBoost	0.70	0.69	0.69	0.68

Bold values refer to the combination of classifier which have better performance.