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. 2018 Oct 28;2018:3640705. doi: 10.1155/2018/3640705

Table 1.

Simplified SegNet network.

S. No. Layer name Type Description
1 “Image input” Image 208 × 1761 images with “zero center” normalization
2 “encoder1_conv1” Convolution 64 3 × 3 × 1 convolutions with stride [1 1] and padding [1 1 1 1]
3 “encoder1_bn_1” Batch normalization Batch normalization with 64 channels
4 “encoder1_relu_1” ReLU ReLU
5 “encoder1_conv2” Convolution 64 3 × 3 × 64 convolutions with stride [1 1] and padding [1 1 1 1]
6 “encoder1_bn_2” Batch normalization Batch normalization with 64 channels
7 “encoder1_relu_2” ReLU ReLU
8 “encoder1_maxpool” Max pooling 2 × 2 max pooling with stride [2 2] and padding [0 0 0 0]
9 “encoder2_conv1” Convolution 64 3 × 3 × 64 convolutions with stride [1 1] and padding [1 1 1 1]
10 “encoder2_bn_1” Batch normalization Batch normalization with 64 channels
11 “encoder2_relu_1” ReLU ReLU
12 “encoder2_conv2” Convolution 64 3× 3 × 64 convolutions with stride [1 1] and padding [1 1 1 1]
13 “encoder2_bn_2” Batch normalization Batch normalization with 64 channels
14 “encoder2_relu_2” ReLU ReLU
15 “encoder2_maxpool” Max pooling 2 × 2 max pooling with stride [2 2] and padding [0 0 0 0]
16 “decoder2_unpool” Max unpooling Max unpooling
17 “decoder2_conv2” Convolution 64 3× 3 × 64 convolutions with stride [1 1] and padding [1 1 1 1]
18 “decoder2_bn_2” Batch normalization Batch normalization with 64 channels
19 “decoder2_relu_2” ReLU ReLU
20 “decoder2_conv1” Convolution 64 3 × 3 × 64 convolutions with stride [1 1] and padding [1 1 1 1]
21 “decoder2_bn_1” Batch normalization Batch normalization with 64 channels
22 “decoder2_relu_1” ReLU ReLU
23 “decoder1_unpool” Max unpooling Max unpooling
24 “decoder1_conv2” Convolution 64 3 × 3 × 64 convolutions with stride [1 1] and padding [1 1 1 1]
25 “decoder1_bn_2” Batch normalization Batch normalization with 64 channels
26 “decoder1_relu_2” ReLU ReLU
27 “decoder1_conv1” Convolution 4 3 × 3 × 64 convolutions with stride [1 1] and padding [1 1 1 1]
28 “decoder1_bn_1” Batch normalization Batch normalization with 4 channels
29 “decoder1_relu_1” ReLU ReLU
30 “Softmax” Softmax Softmax
31 “Pixel_classify” Pixel classification layer Class weighted cross-entropy loss with “background,” “CSF,” “GM,” and “WM” classes