infantSeg at https://github.com/ginobilinie/infantSeg

infant_deploy_singleModality.prototxt

# Simple single-layer network to showcase editing model parameters.
name: "InfantNet"
input: "dataMR32"
input_shape {
  dim: 1
  dim: 1
  dim: 32
  dim: 32
  dim: 32
}

#-------------layer group 1---------------
layer {
  name: "conv1a"
  type: "Convolution"
  bottom: "dataMR32"
  top: "conv1a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1a"
  type: "ReLU"
  bottom: "conv1a"
  top: "conv1a"
}
layer {
  name: "conv1b"
  type: "Convolution"
  bottom: "conv1a"
  top: "conv1b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1b"
  type: "ReLU"
  bottom: "conv1b"
  top: "conv1b"
}
layer {
  name: "conv1c"
  type: "Convolution"
  bottom: "conv1b"
  top: "conv1c"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu1c"
  type: "ReLU"
  bottom: "conv1c"
  top: "conv1c"
}
layer {
  name: "pool1"
  type: "Pooling"
  bottom: "conv1c"
  top: "pool1"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
    engine: CAFFE
  }
}
#-------------layer group 2---------------
layer {
  name: "conv2a"
  type: "Convolution"
  bottom: "pool1"
  top: "conv2a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2a"
  type: "ReLU"
  bottom: "conv2a"
  top: "conv2a"
}
layer {
  name: "conv2b"
  type: "Convolution"
  bottom: "conv2a"
  top: "conv2b"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu2b"
  type: "ReLU"
  bottom: "conv2b"
  top: "conv2b"
}
layer {
  name: "pool2"
  type: "Pooling"
  bottom: "conv2b"
  top: "pool2"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
    engine: CAFFE
  }
}
#-------------layer group 3---------------
layer {
  name: "conv3a"
  type: "Convolution"
  bottom: "pool2"
  top: "conv3a"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    kernel_size: 3
    pad: 1
    stride: 1
    engine: CAFFE
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu3a"
  type: "ReLU"
  bottom: "conv3a"
  top: "conv3a"
}
layer {
  name: "pool3"
  type: "Pooling"
  bottom: "conv3a"
  top: "pool3"
  pooling_param {
    pool: AVE
    kernel_size: 3
    stride: 2
    engine: CAFFE
  }
}
#------------layer group 4-------------
layer {
  name: "deconv4"
  type: "Deconvolution"
  bottom: "pool3"
  top: "deconv4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    #bias_term: false
    engine: CAFFE
    kernel_size: 4
    pad: 1
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "relu4"
  type: "ReLU"
  bottom: "deconv4"
  top: "deconv4"
}
#------------layer group 5-------------
layer {
  name: "deconv5"
  type: "Deconvolution"
  bottom: "deconv4"
  top: "deconv5"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 32
    #bias_term: false
    engine: CAFFE
    kernel_size: 4
    pad: 1
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "relu5"
  type: "ReLU"
  bottom: "deconv5"
  top: "deconv5"
}
#------------layer group 6-------------
layer {
  name: "deconv6"
  type: "Deconvolution"
  bottom: "deconv5"
  top: "deconv6"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 2
  }
  convolution_param {
    num_output: 4
    #bias_term: false
    engine: CAFFE
    kernel_size: 4
    pad: 1
    stride: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "deconv6"
  top: "deconv6"
}

layer {
  name: "softmax"
  type: "Softmax"
  bottom: "deconv6"
  top: "softmax"
  include: { phase: TEST }
}

#layer {
#  name: "loss"
#  type: "SoftmaxWithLoss"
#  bottom: "deconv6"
#  bottom: "dataSeg32"
#  top: "loss"
#  loss_param {
#    ignore_label: -1
#  }
#  softmax_param {
#    axis: 1
#  }
#  include: { phase: TEST }
#}

#layer {
#  name: "frscore"
#  type: "Crop"
#  bottom: "upscore"
#  bottom: "data"
#  top: "score"
#  crop_param {
#    axis: 2
#    offset: 19
#  }
#}