Table 2 Deck two CNN model of ABCDEF feature extraction.

From: DDCNN-F: double decker convolutional neural network 'F' feature fusion as a medical image classification framework

Layers

Descriptions

Activations

convolutional2D_1

Size of (3,3) -32 filters

ReLu

convolutional2D_2

Size of (3,3)- 64 filters

ReLu

max_pooling2D_1

(2,2) pool size

–

convolutional2D_3

Sze of (3,3)- 128 filters

ReLu

max_pooling2d_2

Pool size (2,2)

–

convolutional2D_4

Size of (3,3)- 256 filters

ReLu

max_pooling2d_3

Pool size (2,2)

 

flatten_Layer1

–

–

dense_Layer1

256 units

ReLu

dense_Layer2

128 units

ReLu

dense_Layer3

64 units

ReLu

dense_Layer4

32 units

ReLu

dense_Layer5

2 units

Sigmoid

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