A Siamese neural network is a neural network architecture that runs two pieces of data through identical neural networks, and then the outputs are fed to a loss function measuring similarity between outputs.

Siamese neural networks are a common model architecture for one-shot learning.

For example, a Siamese neural network might be used to train a model to measure similarity between two different images, for the purpose of identifying whether the images are of the object…. but without training on many examples of that object.