name: "GOTURN"
input: "data1"
input_dim: 1
input_dim: 3
input_dim: 227
input_dim: 227
input: "data2"
input_dim: 1
input_dim: 3
input_dim: 227
input_dim: 227
layer {
name: "conv11"
type: "Convolution"
bottom: "data1"
top: "conv11"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu11"
type: "ReLU"
bottom: "conv11"
top: "conv11"
}
layer {
name: "pool11"
type: "Pooling"
bottom: "conv11"
top: "pool11"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm11"
type: "LRN"
bottom: "pool11"
top: "norm11"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv12"
type: "Convolution"
bottom: "norm11"
top: "conv12"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu12"
type: "ReLU"
bottom: "conv12"
top: "conv12"
}
layer {
name: "pool12"
type: "Pooling"
bottom: "conv12"
top: "pool12"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm12"
type: "LRN"
bottom: "pool12"
top: "norm12"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv13"
type: "Convolution"
bottom: "norm12"
top: "conv13"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu13"
type: "ReLU"
bottom: "conv13"
top: "conv13"
}
layer {
name: "conv14"
type: "Convolution"
bottom: "conv13"
top: "conv14"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu14"
type: "ReLU"
bottom: "conv14"
top: "conv14"
}
layer {
name: "conv15"
type: "Convolution"
bottom: "conv14"
top: "conv15"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu15"
type: "ReLU"
bottom: "conv15"
top: "conv15"
}
layer {
name: "pool15"
type: "Pooling"
bottom: "conv15"
top: "pool15"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "conv21"
type: "Convolution"
bottom: "data2"
top: "conv21"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 96
kernel_size: 11
stride: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu21"
type: "ReLU"
bottom: "conv21"
top: "conv21"
}
layer {
name: "pool21"
type: "Pooling"
bottom: "conv21"
top: "pool21"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm21"
type: "LRN"
bottom: "pool21"
top: "norm21"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv22"
type: "Convolution"
bottom: "norm21"
top: "conv22"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 2
kernel_size: 5
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu22"
type: "ReLU"
bottom: "conv22"
top: "conv22"
}
layer {
name: "pool22"
type: "Pooling"
bottom: "conv22"
top: "pool22"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "norm22"
type: "LRN"
bottom: "pool22"
top: "norm22"
lrn_param {
local_size: 5
alpha: 0.0001
beta: 0.75
}
}
layer {
name: "conv23"
type: "Convolution"
bottom: "norm22"
top: "conv23"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "relu23"
type: "ReLU"
bottom: "conv23"
top: "conv23"
}
layer {
name: "conv24"
type: "Convolution"
bottom: "conv23"
top: "conv24"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 384
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu24"
type: "ReLU"
bottom: "conv24"
top: "conv24"
}
layer {
name: "conv25"
type: "Convolution"
bottom: "conv24"
top: "conv25"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
convolution_param {
num_output: 256
pad: 1
kernel_size: 3
group: 2
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu25"
type: "ReLU"
bottom: "conv25"
top: "conv25"
}
layer {
name: "pool25"
type: "Pooling"
bottom: "conv25"
top: "pool25"
pooling_param {
pool: MAX
kernel_size: 3
stride: 2
}
}
layer {
name: "concat1"
type: "Concat"
bottom: "pool15"
bottom: "pool25"
top: "poolConcat"
}
layer {
name: "fc6"
type: "InnerProduct"
bottom: "poolConcat"
top: "fc6"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu6"
type: "ReLU"
bottom: "fc6"
top: "fc6"
}
layer {
name: "drop6"
type: "Dropout"
bottom: "fc6"
top: "fc6"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc7"
type: "InnerProduct"
bottom: "fc6"
top: "fc7"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4096
weight_filler {
type: "gaussian"
std: 0.005
}
bias_filler {
type: "constant"
value: 1
}
}
}
layer {
name: "relu7"
type: "ReLU"
bottom: "fc7"
top: "fc7"
}
layer {
name: "drop7"
type: "Dropout"
bottom: "fc7"
top: "fc7"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "fc8"
type: "InnerProduct"
bottom: "fc7"
top: "fc8"
param {
lr_mult: 1
decay_mult: 1
}
param {
lr_mult: 2
decay_mult: 0
}
inner_product_param {
num_output: 4
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "scale"
bottom: "fc8"
top: "out"
type: "Power"
power_param {
power: 1
scale: 10
shift: 0
}
}
