Table 5.

Classification performances of the 10-fold machine learning classifiers on features extracted from each of the five pre-trained deep models.

Feature Extractor	Classifier	Accuracy	Sensitivity	Specificity	Precision	F1-Score
AlexNet	NB	${\displaystyle 0.6695\pm 0.0097}$	${\displaystyle 0.5323\pm 0.0172}$	${\displaystyle 0.7866\pm 0.0114}$	${\displaystyle 0.6806\pm 0.0133}$	${\displaystyle 0.5969\pm 0.0139}$
	SVM	${\displaystyle 0.6880\pm 0.0139}$	${\displaystyle 0.6894\pm 0.0216}$	${\displaystyle 0.6868\pm 0.0168}$	${\displaystyle 0.6530\pm 0.0145}$	${\displaystyle 0.6702\pm 0.0157}$
	LDA	${\displaystyle 0.7100\pm 0.0070}$	${\displaystyle 0.6934\pm 0.0116}$	${\displaystyle 0.7241\pm 0.0121}$	${\displaystyle 0.6826\pm 0.0091}$	${\displaystyle 0.6877\pm 0.0076}$
	DT	${\displaystyle 0.6503\pm 0.0187}$	${\displaystyle 0.6160\pm 0.0290}$	${\displaystyle 0.6795\pm 0.0270}$	${\displaystyle 0.6226\pm 0.0215}$	${\displaystyle 0.6180\pm 0.0214}$
GoogleNet	NB	${\displaystyle 0.7176\pm 0.0101}$	${\displaystyle 0.5689\pm 0.0139}$	${\displaystyle 0.8446\pm 0.0149}$	${\displaystyle 0.7589\pm 0.0180}$	${\displaystyle 0.6497\pm 0.0124}$
	SVM	${\displaystyle 0.6592\pm 0.0085}$	${\displaystyle 0.5366\pm 0.0128}$	${\displaystyle 0.7639\pm 0.0111}$	${\displaystyle 0.6602\pm 0.0122}$	${\displaystyle 0.5917\pm 0.0110}$
	LDA	${\displaystyle 0.7276\pm 0.0072}$	${\displaystyle 0.6129\pm 0.0126}$	${\displaystyle 0.8256\pm 0.0082}$	${\displaystyle 0.7502\pm 0.0094}$	${\displaystyle 0.6743\pm 0.0097}$
	DT	${\displaystyle 0.6725\pm 0.0237}$	${\displaystyle 0.6471\pm 0.0321}$	${\displaystyle 0.6941\pm 0.0345}$	${\displaystyle 0.6464\pm 0.0288}$	${\displaystyle 0.6450\pm 0.0252}$
InceptionV3	NB	${\displaystyle 0.6495\pm 0.0150}$	${\displaystyle 0.5280\pm 0.0207}$	${\displaystyle 0.7532\pm 0.0205}$	${\displaystyle 0.6475\pm 0.0214}$	${\displaystyle 0.5808\pm 0.0182}$
	SVM	${\displaystyle 0.6907\pm 0.0100}$	${\displaystyle 0.6094\pm 0.0169}$	${\displaystyle 0.7600\pm 0.0121}$	${\displaystyle 0.6846\pm 0.0122}$	${\displaystyle 0.6444\pm 0.0129}$
	LDA	${\displaystyle 0.7083\pm 0.0068}$	${\displaystyle 0.6554\pm 0.0086}$	${\displaystyle 0.7534\pm 0.0109}$	${\displaystyle 0.6945\pm 0.0096}$	${\displaystyle 0.6742\pm 0.0070}$
	DT	${\displaystyle 0.6589\pm 0.0260}$	${\displaystyle 0.6583\pm 0.0383}$	${\displaystyle 0.6595\pm 0.0327}$	${\displaystyle 0.6238\pm 0.0270}$	${\displaystyle 0.6391\pm 0.0287}$
ResNet50	NB	${\displaystyle 0.6688\pm 0.0085}$	${\displaystyle 0.8689\pm 0.0138}$	${\displaystyle 0.4980\pm 0.0125}$	${\displaystyle 0.5965\pm 0.0066}$	${\displaystyle 0.7072\pm 0.0079}$
	SVM	${\displaystyle 0.6197\pm 0.0157}$	${\displaystyle 0.5600\pm 0.0251}$	${\displaystyle 0.6707\pm 0.0232}$	${\displaystyle 0.5930\pm 0.0186}$	${\displaystyle 0.5750\pm 0.0189}$
	LDA	${\displaystyle 0.6895\pm 0.0094}$	${\displaystyle 0.7903\pm 0.0306}$	${\displaystyle 0.6034\pm 0.0169}$	${\displaystyle 0.6298\pm 0.0069}$	${\displaystyle 0.7000\pm 0.0144}$
	DT	${\displaystyle 0.6161\pm 0.0207}$	${\displaystyle 0.5891\pm 0.0298}$	${\displaystyle 0.6390\pm 0.0313}$	${\displaystyle 0.5838\pm 0.0239}$	${\displaystyle 0.5851\pm 0.0229}$
XceptionNet	NB	${\displaystyle 0.6849\pm 0.0087}$	${\displaystyle 0.7726\pm 0.0142}$	${\displaystyle 0.6100\pm 0.0094}$	${\displaystyle 0.6284\pm 0.0075}$	${\displaystyle 0.6929\pm 0.0094}$
	SVM	${\displaystyle 0.6868\pm 0.0105}$	${\displaystyle 0.7931\pm 0.0170}$	${\displaystyle 0.5961\pm 0.0102}$	${\displaystyle 0.6263\pm 0.0085}$	${\displaystyle 0.6998\pm 0.0112}$
	LDA	${\displaystyle 0.7496\pm 0.0119}$	${\displaystyle 0.8051\pm 0.0193}$	${\displaystyle 0.7022\pm 0.0133}$	${\displaystyle 0.6978\pm 0.0113}$	${\displaystyle 0.7473\pm 0.0131}$
	DT	${\displaystyle 0.6253\pm 0.0219}$	${\displaystyle 0.5806\pm 0.0320}$	${\displaystyle 0.6634\pm 0.0298}$	${\displaystyle 0.5967\pm 0.0251}$	${\displaystyle 0.5872\pm 0.0254}$