Table 12.

State-of-the-art Lung Classification Models.

Work	Method	Network	Class#	Data	Para#	Aug	Feature	Results
Dalal (2018) [32]	Ensemble	SVM, KNN, GMM, CNN	7	R.A.L.E data	NA	✓	MFCC, LBP	ACC: 95.56%
Hai (2019) [35]	NA	ResNet50	3	489	+23 M		Sp	ACC: 98.79%
Fatih (2020) [36]	Ensemble	CNN	4	920	NA		Sp Images, Deep Features	ACC: 71.15%
Demir (2020) [37]	NA	CNN, SVM	4	6898	138 M		Sp	ACC: 65.9%
Demir (2020) [37]	Transfer learning	CNN, SVM	4	6898	138 M		Sp Images	ACC: 63.09%
Samiul (2020) [38]	NA	CNN	6	917	3.8 M	✓	Hybrid Scalogram	98.70%
Luay (2021) [40]	Ensemble	SVM, KNN, DT, KNN	6	308/1176	NA		Entropy features	ACC: 98.20%
FDC-FS (Ours)	Fusion	DCNN	6	Original (Augmented): 919 (10,109)	1.48 M	✓	SP, MFCC, CH	ACC: 99.1%