Abstract
This paper proposes a specialized artificial neural network layer named
SimilarNet, designed to compare two feature vectors while considering
the positions of their elements to produce an output in a vector format.
By leveraging the advantages of the cosine similarity and concatenation
layer, SimilarNet can effectively compare two vectors, enabling the
construction of trained comparison models using multidimensional
activation functions. In addition, SimilarNet can realize 1:1
comparisons of data with different shapes, unlike cosine similarity.