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One-Shot-Face-Recognition

One-Shot Face Recognition Using Siamese Neural Networks

In this work, we used convolutional neural networks (CNNs) to carry out the task of facial recognition. More specifically, we have implemented a one-shot classification solution. In order to achieve this goal, we implemented a Siamese Neural Network(SNN), according to the paper: Siamese Neural Networks for One-shot Image recognition Our main goal was to successfully execute a one-shot learning task for previously unseen objects. Given two facial image of previously unseen persons, our SNN will try and determine whether they are the same person.

Sklearn API: In order to use the dataset with sklearn, we have changed the function fetch_lfw_pairs:

  1. Change the function that will support one channel picture
    • the change in sklearn\datasets\lfw.py --> new file of lfw was added to repo with comment added code
  2. Redirector / Change to our dataset LFW-a instead of the existing one, and not download the matching dataset (LFW).

siamese neural networks

references:

  1. Siamese Neural Networks for One-shot Image Recognition
  2. Contrastive Loss

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