Table 1.

Summary table for the hyper-tuning of parameters for Support Vector Machines (SVM’s).

Model	Image size	Kernel radial basis function	Cost function	Accuracy	Precision	Recall	F1 score	Time elapsed (Seconds)
SVM	32	RBF	4	97.17	97.54	97.17	97.19	0.017
SVM	64	RBF	2.5	97.74	97.77	97.74	97.70	0.021
SVM	128	RBF	2.5	97.74	97.77	97.74	97.70	0.019
SVM	256	RBF	2.5	97.74	97.77	97.74	97.70	0.018
SVM	512	RBF	2.5	97.74	97.77	97.74	97.70	0.019