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Table 2 Detailed information on CNN model employed for “C-1” mode

From: A hybrid deep CNN model for brain tumor image multi-classification

Layer Name

CNN Layer

Activations

Parameters (Trainable)

Total No. of Trainable Parameters

Input

227 × 227 × 3

227 × 227 × 3

nil

0

Convolutional

128 (6 × 6 × 3), stride of (4,4), with (0 0 0 0) padding

56 × 56 × 128

6 × (6 × 3) × 128 weights, 1 × 1 × 128 bias

13,954

Activation layer

Activation layer-1

56 × 56 × 128

nil

0

Normalization

Normalization (cross-channel)

56 × 56 × 128

nil

0

Max_pooling

(2 × 2) with stride of (2,2), and (0 0 0 0) padding

28 × 28 × 128

nil

0

Convolutional

96 (6 × 6 × 128), stride of (1,1), and (2 2 2 2) padding

31 × 31 × 96

2 × (2 × 128) × 96 weights, 1 × 1 × 96 bias

49,246

Activation layer

Activation layer-2

31 × 31 × 96

nil

0

Max_pooling

(2 × 2) with stride of (2,2), and (0 0 0 0) padding

15 × 15 × 96

nil

0

Fully_connected

512 Fully_connected

1 × 1 × 512

512 × 21,700 weights, 512 × 1 bias

11,060,714

Dropout

30%

1 × 1 × 512

nil

0

Fully_connected

2 Fully_connected

1 × 1 × 2

512 × 2 weights, 2 × 1 bias

1026

Softmax

Softmax

1 × 1 × 2

nil

0

Classification

Tumor or non-tumor

nil

nil

0