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Table 1 Alex-Network Architecture: Input Dimension & Number of Kernels

From: Atrial fibrillation classification based on convolutional neural networks

Layer/Model

Alex 1

Alex 2

Alex 3

Alex 4

Alex 5

Alex 6

Convolution

(1, 500, 96)a

(1, 500, 48)

(1, 500, 24)

(1, 500, 12)

(1, 500, 6)

(1, 500, 3)

Pooling

(1, 250, 96)

(1, 250, 48)

(1, 250, 24)

(1, 250, 12)

(1, 250, 6)

(1, 250, 3)

Convolution

(1, 250, 256)

(1, 250, 128)

(1, 250, 64)

(1, 250, 32)

(1, 250, 16)

(1, 250, 8)

Pooling

(1, 125, 256)

(1, 125, 128)

(1, 125, 64)

(1, 125, 32)

(1, 125, 16)

(1, 125, 8)

Convolution

(1, 125, 384)

(1, 125, 192)

(1, 125, 96)

(1, 125, 48)

(1, 125, 24)

(1, 125, 12)

Convolution

(1, 125, 384)

(1, 125, 192)

(1, 125, 96)

(1, 125, 48)

(1, 125, 24)

(1, 125, 12)

Convolution

(1, 125, 256)

(1, 125, 128)

(1, 125, 64)

(1, 125, 32)

(1, 125, 16)

(1, 125, 8)

Pooling

(1, 63, 256)

(1, 63, 128)

(1, 63, 64)

(1, 63, 32)

(1, 63, 16)

(1, 63, 8)

Fully Connected

(1024)

(1024)

(1024)

(1024)

(1024)

(1024)

Fully Connected

(1024)

(1024)

(1024)

(1024)

(1024)

(1024)

Output

(2)

(2)

(2)

(2)

(2)

(2)

  1. a(1, 500, 96) Input Dimension 1, Input Dimension 2, Number of Kernels