DRPNN_net.prototxt

name: "DRPNN"
layer {
  name: "data"
  type: "HDF5Data"
  top: "data" 
  top: "label"
  hdf5_data_param {
    source: "/Pansharpening and SR/Pansharpening/train_QBfusion.txt"
    batch_size: 64
  }
  include: { phase: TRAIN }
}

layer {
  name: "conv1"
  type: "Convolution"
  bottom: "data1"
  top: "conv1"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu1"
  type: "ReLU"
  bottom: "conv1"
  top: "conv1"
}

layer {
  name: "conv2"
  type: "Convolution"
  bottom: "conv1"
  top: "conv2"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu2"
  type: "ReLU"
  bottom: "conv2"
  top: "conv2"
}

layer {
  name: "conv3"
  type: "Convolution"
  bottom: "conv2"
  top: "conv3"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu3"
  type: "ReLU"
  bottom: "conv3"
  top: "conv3"
}

layer {
  name: "conv4"
  type: "Convolution"
  bottom: "conv3"
  top: "conv4"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu4"
  type: "ReLU"
  bottom: "conv4"
  top: "conv4"
}

layer {
  name: "conv5"
  type: "Convolution"
  bottom: "conv4"
  top: "conv5"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu5"
  type: "ReLU"
  bottom: "conv5"
  top: "conv5"
}

layer {
  name: "conv6"
  type: "Convolution"
  bottom: "conv5"
  top: "conv6"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu6"
  type: "ReLU"
  bottom: "conv6"
  top: "conv6"
}

layer {
  name: "conv7"
  type: "Convolution"
  bottom: "conv6"
  top: "conv7"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu7"
  type: "ReLU"
  bottom: "conv7"
  top: "conv7"
}

layer {
  name: "conv8"
  type: "Convolution"
  bottom: "conv7"
  top: "conv8"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu8"
  type: "ReLU"
  bottom: "conv8"
  top: "conv8"
}

layer {
  name: "conv9"
  type: "Convolution"
  bottom: "conv8"
  top: "conv9"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 64
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "relu9"
  type: "ReLU"
  bottom: "conv9"
  top: "conv9"
}

layer {
  name: "conv10"
  type: "Convolution"
  bottom: "conv9"
  top: "conv10"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 10
    kernel_size: 7
    stride: 1
    pad: 3
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
	name: "sum"
	type: "Eltwise"
	bottom: "data"
	bottom: "conv10"
	top: "sum"
	eltwise_param {
	  operation: 1
	}
}

layer {
  name: "relu10"
  type: "ReLU"
  bottom: "conv10"
  top: "conv10"
}

layer {
  name: "conv11"
  type: "Convolution"
  bottom: "conv10"
  top: "conv11"
  param {
    lr_mult: 1
  }
  param {
    lr_mult: 0.1
  }
  convolution_param {
    num_output: 6
    kernel_size: 3
    stride: 1
    pad: 0
    weight_filler {
      type: "msra"
    }
    bias_filler {
      type: "constant"
    }
  }
}

layer {
  name: "loss"
  type: "EuclideanLoss"
  bottom: "conv11"
  bottom: "label"
  top: "loss"
}