person-re-ranking/caffe/docs/tutorial/layers/lrn.md

title
Local Response Normalization (LRN)

Local Response Normalization (LRN)

• Layer type: LRN
• Doxygen Documentation
• Header: ./include/caffe/layers/lrn_layer.hpp
• CPU Implementation: ./src/caffe/layers/lrn_layer.cpp
• CUDA GPU Implementation: ./src/caffe/layers/lrn_layer.cu
• Parameters (LRNParameter lrn_param)
  • Optional
    • local_size [default 5]: the number of channels to sum over (for cross channel LRN) or the side length of the square region to sum over (for within channel LRN)
    • alpha [default 1]: the scaling parameter (see below)
    • beta [default 5]: the exponent (see below)
    • norm_region [default ACROSS_CHANNELS]: whether to sum over adjacent channels (ACROSS_CHANNELS) or nearby spatial locaitons (WITHIN_CHANNEL)

The local response normalization layer performs a kind of "lateral inhibition" by normalizing over local input regions. In ACROSS_CHANNELS mode, the local regions extend across nearby channels, but have no spatial extent (i.e., they have shape local_size x 1 x 1). In WITHIN_CHANNEL mode, the local regions extend spatially, but are in separate channels (i.e., they have shape 1 x local_size x local_size). Each input value is divided by (1 + (\alpha/n) \sum_i x_i^2)^\beta$, where n$ is the size of each local region, and the sum is taken over the region centered at that value (zero padding is added where necessary).

Parameters

• Parameters (LRNParameter lrn_param)
• From ./src/caffe/proto/caffe.proto:

{% highlight Protobuf %} {% include proto/LRNParameter.txt %} {% endhighlight %}