N way K Shot: Siamese Network with Contrastive Loss for pokemon Classification

When we have a tiny dataset, Few shot learning can be applied. A Siamese network with contrastive loss is one of the few-shot learning algorithms. Let's first examine the differences between Neural networks and Siamese networks before briefly moving on to Siamese. This is merely an intuitive understanding of the siamese network; the preprocessing and training will differ slightly from those of neural networks, and I'll go into more detail about how it functions in a moment. Deep learning is always data-hungry; the more data, the better the performance. For neural network training, we need at least a few thousand data; otherwise, the network will overfit, and even with regularisation and fine-tuning, Low precision is expected.