SiaCeption - Siamese Networks Based on Pretrained ConvNets

Development of few-shot learning tool for a variety of image classes, utitilizing features extracted from ConvNets. This is specifically for my school Comenius project.

A big problem currently in the field of ML is the fact that a lot of data is required to train image classification neural networks. By using a siamese network approach in this project, I hope to make algorithms that require (as shown in the test) only a single image (although a few more do increase the accuracy) to train.

Follow the attached jupyter notebook to understand the algorithm and go through an example on a bunch of animals. (Developed with only 1 image for training each class =)