Now that we have a basic understanding of siamese networks, we will explore them in detail. The architecture of a siamese network is shown in the following figure:
As you can see in the preceding figure, a siamese network consists of two identical networks, both sharing the same weights and architecture. Let's say we have two inputs, 
and 
. We feed Input 
to Network 
, that is, 
, and we feed Input 
to Network 
, that is, 
.
As you can see, both of these networks have the same weights, 
, and they will generate embeddings for our input, 
and 
. Then, we feed these embeddings to the energy function, 
, which will give us similarity between the two inputs. It can be expressed as follows:
Let's say we use Euclidean distance as our energy function; then the value of will be low if and are similar. The value of will be large if the input values...
