I have to find the closest match between my image and bunch of already collected images of different classes in the folder. Whic meta-learning approach should I select. I am thinking about the Siamese or matching network. In Siamese, I have to match my image with all existing images in the folder to find the correct match. So do you think if 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 the time of the test new unseen images class can be added on which model is not trained. Do you think a matching network will still work for this case?