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SE_ResNeXt_3D

2020-02-24 | |  32 |   0 |   0

SE_ResNeXt_3D

The origin of SENet

Code modified from 2d se-resnext

Note

The first layer was changed to ResNet-like structure due to the high memory cost.

  • Before:

  x = conv_layer(x, filter=64, kernel=[3, 3], stride=1, layer_name=scope+'_conv1')
  x = Batch_Normalization(x, training=self.training, scope=scope+'_batch1')

  • After:

  x = Conv3D(filters=self.init_filters, kernel_size=(7, 7, 7), strides=(2, 2, 2), padding='same')(x)
  x = MaxPooling3D(pool_size=(3, 3, 3), strides=(2, 2, 2), padding="same")(x)
  x = Batch_Normalization(x, training=self.training, scope=scope+'_batch1')


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