I am not sure how I would do it your way with a neuron that directly classifies seen or unseen.
However, an unsupervised way would be to overfit an autoencoder to some dataset. The idea is that given a sample from the training set, it will achieve a very low loss. Given an unseen sample it would get a very high loss.