/Face-Recognition-using-Siamese-Networks

This project aims to perform reliable facial recognition using minimal training data. An example of few-shot learning, this algorithm is able to distinguish between faces by using a dataset having only 10 instances of each face. This project uses Siamese networks to compute the similarity between 2 facial images and classify them accordingly. The algorithm implemented can be easily extended to many real world use cases like signature verification, text similarity with only minimal data points.

Primary LanguagePython

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