Face Recognition as Binary Classification

Face Recognition can also be looked at as a binary classification problem.

We know that the Siamese Network outputs a pair of encodings, one for each image.

These encodings can be used to train a Logistic Regression classifier with labels 0 (not same person) and 1 (same person), instead of using the triplet loss function for training.

The Logistic Regression equation for this problem would be:

y^=σ(k=1num_featureswif(x(i))kf(x(j))k+b)\hat{y} = \sigma (\sum_{k=1}^{num\_features} w_i |f(x^{(i)})_k-f(x^{(j)})_k| + b)

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