I have to find the closest match between my image and a bunch of already collected images of different classes in the folder.
Which of the meta-learning approach should I select?
So, do you think that I can use a matching network and produce a better result? What is the parameter based on which developer decides where to use matching/prototypical network and where to use Siamese network?
Note: at testing time, new unseen images classes can be added on which model is not trained. Do you think a matching network will still work for this case?