Table 2.

Comparison of hyperparameters between proposed and existing transfer learning framework.

Hyperparameter	Existing transfer learning models						Proposed model
	VGG19	InceptionV3	DenseNet169	ResNet50V2	Xception	MobileNetV2
Input shape	(224,224,3)	(299,299,3)	(224,224,3)	(224,224,3)	(299,299,3)	(224,224,3)	(224,224,3)
Model size	1.5GB	250 MB	152.75 MB	270 MB	250.6 MB	27.57 MB	11.72 MB
Total parameters	143 0667 240	23 851 784	14 307 880	25 613 800	22 910 480	3 538 984	961 923
Epochs	30						30
Batch size	32						32
Loss	Categorical crossentropy						Categorical crossentropy
Optimizer	Adam (lr $=$ 0.001)						Adam (lr $=$ 0.001)
Learning rate	$L=L_0/\left(10^{(epoch/10)}\right)$, $L_0=0.001$						$L=L_0/\left(10^{(epoch/10)}\right)$, $L_0=0.001$