Table 1.

The sizes of the input layers of the five deep learning architectures and the name of the layers where features were obtained and the mined features sizes.

CNN Architecture	Size of Input	Feature Extraction Layer Name	Feature Extraction Layer Description	Size of Features
ResNet-50	224x224x3	“avg_pool”	Last average pooling layer	2048
		“new_fc”	Last fully connected layer	Binary
				2
				Multiclass
				3
DenseNet-201	224x224x3	“avg_pool”	Last average pooling layer	1920
		“new_fc”	Last fully connected layer	Binary
				2
				Multiclass
				3
Inception-V3	229x229x3	“avg_pool"	Last average pooling layer	2048
		“new_fc”	Last fully connected layer	Binary
				2
				Multiclass
				3
Xception	229x229x3	“avg_pool"	Last average pooling layer	2048
		“new_fc”	Last fully connected layer	Binary
				2
				Multiclass
				3
Inception-ResNet	229x229x3	“avg_pool”	Last average pooling layer	1536
		“new_fc”	Last fully connected layer	Binary
				2
				Multiclass
				3