COVID-19 Semantic Pneumonia Segmentation and Classification Using Artificial Intelligence

Table 7

Comparison between proposed model and related works.

N	Ref.	Model techniques	Average accuracy	Running time (min)
1	[15]	Truncated inception network	98.5	110
2	[16]	DarkCovidNet	87.02	-
3	[9]	Bayes-SqueezeNet	97.9	-
4	[17]	DenseNet	85
5	[18]	MobileNet	94.7	40
6	[19]	Resnet-50 + SVM	94.7	52
7	[20]	CXRVN	97.5	45
8	[33]	Weighted average pruned	98.1	38
9	Our model	Semantic segmentation + (ResNet 50 and DenseNet) + weighted average pruned	99.6	48