deploy.prototxt

name: "MCNN"
input: "data"
input_dim:1 
input_dim:3
input_dim:1000
input_dim:1000
#state {
#  phase: TEST
#}
layer {
  name: "conv1_1"
  type: "Convolution"
  bottom: "data"
  #bottom: "image"
  top: "conv1_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 24
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool1_1"
  type: "Pooling"
  bottom: "conv1_1"
  top: "pool1_1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "relu1_1"
  type: "ReLU"
  bottom: "pool1_1"
  top: "pool1_1"
}
layer {
  name: "conv1_2"
  type: "Convolution"
  bottom: "pool1_1"
  top: "conv1_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 48
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool1_2"
  type: "Pooling"
  bottom: "conv1_2"
  top: "pool1_2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "relu1_2"
  type: "ReLU"
  bottom: "pool1_2"
  top: "pool1_2"
}
layer {
  name: "conv1_3"
  type: "Convolution"
  bottom: "pool1_2"
  top: "conv1_3"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 24
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1_3"
  type: "ReLU"
  bottom: "conv1_3"
  top: "conv1_3"
}
layer {
  name: "conv1_4"
  type: "Convolution"
  bottom: "conv1_3"
  top: "conv1_4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 12
    pad: 1
    kernel_size: 3
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1_4"
  type: "ReLU"
  bottom: "conv1_4"
  top: "conv1_4"
}

#-----------------------------colunm2(M)
layer {
  name: "conv2_1"
  type: "Convolution"
  bottom: "data"
  #bottom: "image"
  top: "conv2_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 20
    pad: 3
    kernel_size: 7
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool2_1"
  type: "Pooling"
  bottom: "conv2_1"
  top: "pool2_1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "relu2_1"
  type: "ReLU"
  bottom: "pool2_1"
  top: "pool2_1"
}
layer {
  name: "conv2_2"
  type: "Convolution"
  bottom: "pool2_1"
  top: "conv2_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 40
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool2_2"
  type: "Pooling"
  bottom: "conv2_2"
  top: "pool2_2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "relu2_2"
  type: "ReLU"
  bottom: "pool2_2"
  top: "pool2_2"
}
layer {
  name: "conv2_3"
  type: "Convolution"
  bottom: "pool2_2"
  top: "conv2_3"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 20
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_3"
  type: "ReLU"
  bottom: "conv2_3"
  top: "conv2_3"
}
layer {
  name: "conv2_4"
  type: "Convolution"
  bottom: "conv2_3"
  top: "conv2_4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 10
    pad: 2
    kernel_size: 5
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2_4"
  type: "ReLU"
  bottom: "conv2_4"
  top: "conv2_4"
}
#-------------------------------colunm3(L)
layer {
  name: "conv3_1"
  type: "Convolution"
  bottom: "data"
  #bottom: "image"
  top: "conv3_1"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 16
    pad: 4
    kernel_size: 9
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool3_1"
  type: "Pooling"
  bottom: "conv3_1"
  top: "pool3_1"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "relu3_1"
  type: "ReLU"
  bottom: "pool3_1"
  top: "pool3_1"
}
layer {
  name: "conv3_2"
  type: "Convolution"
  bottom: "pool3_1"
  top: "conv3_2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    pad: 3
    kernel_size: 7
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "pool3_2"
  type: "Pooling"
  bottom: "conv3_2"
  top: "pool3_2"
  pooling_param {
    pool: MAX
    kernel_size: 2
    stride: 2
  }
}
layer {
  name: "relu3_2"
  type: "ReLU"
  bottom: "pool3_2"
  top: "pool3_2"
}
layer {
  name: "conv3_3"
  type: "Convolution"
  bottom: "pool3_2"
  top: "conv3_3"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 16
    pad: 3
    kernel_size: 7
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_3"
  type: "ReLU"
  bottom: "conv3_3"
  top: "conv3_3"
}
layer {
  name: "conv3_4"
  type: "Convolution"
  bottom: "conv3_3"
  top: "conv3_4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 8
    pad: 3
    kernel_size: 7
    stride: 1
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3_4"
  type: "ReLU"
  bottom: "conv3_4"
  top: "conv3_4"
}

layer {
  name: "merge"
  type: "Concat"
  bottom: "conv1_4"
  bottom: "conv2_4"
  bottom: "conv3_4"
  top: "merge"
  concat_param {
    concat_dim: 1
  }
}
layer {
  name: "convo"
  type: "Convolution"
  bottom: "merge"
  top: "convo"
  convolution_param {
    num_output: 1
    kernel_size:1
    stride: 1
    pad: 0
    weight_filler {
      type: "gaussian"
      std: 0.01000000
    }
  }
}
layer {
  name: "reclu"
  type: "ReLU"
  bottom: "convo"
  top: "convo"
}