Table 2.

CNN layers for the four architectures

LeNet-5 ([19])	EEGNet ([18])	DeepConvNet(EEG) ([32])	AlexNet ([17])
Input	Input	Input	Input
Conv2D	Conv2D	Conv2D	Conv2D
AveragePooling2D	BatchNorm	Conv2D	MaxPooling2D
Conv2D	DepthwiseConv2D	BatchNorm	BatchNorm
AveragePooling2D	BatchNorm	MaxPooling2D	Conv2D
Flatten	AveragePool2D	Dropout	MaxPooling2D
Dense	Dropout	Conv2D	BatchNorm
Dense	SeparableConv2D	BatchNorm	Conv2D
Dense	BatchNorm	MaxPooling2D	MaxPooling2D
	AveragePool2D	Dropout	BatchNorm
	Dropout	Conv2D	Conv2D
	Flatten	BatchNorm	BatchNorm
	Dense	MaxPooling2D	Conv2D
		Dropout	BatchNorm
		Conv2D	Conv2D
		BatchNorm	MaxPooling2D
		MaxPooling2D	BatchNorm
		Dropout	Flatten
		Flatten	Dense
		Dense	Dropout
			BatchNorm
			Dense
			Dropout
			BatchNorm
			Dense
			Dropout
			BatchNorm
			Dense