Table 4.

The FNR and the other metrics of the CNNs on the NINA and NIA datasets are reported. The image improvement techniques are active

IIQ not active
Net	Data augmentation	SN	SP	PPV	FDR	FNR	FPR
AlexNet	None	0.87	0.90	0.86	0.15	0.13	0.10
	Yes	0.84	0.91	0.87	0.14	0.16	0.09
DenseNet	None	0.56	0.82	0.77	0.23	0.29	0.18
	Yes	0.64	0.74	0.56	0.44	0.19	0.26
Google InceptionV3	None	0.73	0.76	0.62	0.38	0.27	0.24
	Yes	0.39	0.60	0.29	0.71	0.57	0.40
GoogleNet	None	0.79	0.82	0.72	0.28	0.21	0.18
	Yes	0.45	0.63	0.48	0.52	0.54	0.37
MobileNet	None	0.81	0.72	0.45	0.55	0.14	0.28
	Yes	0.32	0.61	0.29	0.71	0.37	0.38
ShuffleNet	None	0.61	0.74	0.60	0.40	0.35	0.26
	Yes	0.36	0.60	0.45	0.55	0.52	0.39
SqueezeNet	None	0.23	0.43	0.43	0.57	0.22	0.27
	Yes	0.43	0.62	0.41	0.59	0.41	0.37
VGG	None	0.58	0.83	0.76	0.24	0.27	0.17
	Yes	0.82	0.59	0.40	0.60	0.07	0.24