Table 2.

Comparison of proposed innovation with famous state-of-the art models.

Paper	Model	Method	${\mathit{\eta }}_{\mathit{p}} (\%)$	${\mathit{\eta }}_{\mathit{w}} (\%)$	${\mathit{\eta }}_{\mathit{t}\mathit{o}\mathit{t}\mathit{a}\mathit{l}} (\%)$
Babaie et al. [7]	CNN	Train from scratch	64.98	64.75	42.07
Kieffer et al. [37]	VGG-16	Feature Extractor	65.21	64.96	42.36
Kieffer et al. [37]	VGG-16	Fine-tuning	63.85	66.23	42.29
Kieffer et al. [37]	Inception-V3	Feature Extractor	70.94	72.24	50.54
Kieffer et al. [37]	Inception-v3	Fine-tuning	74.87	76.10	56.98
Simonyan et al. [8]	VGG-16 base model	Train from scratch	69.89	71.09	49.68
Szegedy et al. [9]	Inception-V3 base model	Train from scratch	72.65	73.00	53.03
Proposed model	VGG-16	Feature Extractor	77.41	71.27	55.17
Proposed model	Inception-V3	Feature Extractor	79.90	71.33	57.00