Learning from Scarce Information: Using Synthetic Data to Classify Roman Fine Ware Pottery
In this article, we consider a version of the challenging problem of learning from datasets whose size is too limited to allow generalisation beyond the training set.To address the challenge, we propose to maison alhambra libbra use a transfer learning approach whereby the model is first trained on a synthetic dataset replicating features of the or