Tensorflow: How to have n number of image inputs to determine 1 output: handwriting data matching [closed]

In this case, we can use a Siamese Neural Network to match a given signature with N other images of the same signature ( provided by the user ). A Siamese Neural network takes in two images and outputs a similarity score in [ 0, 1 ] for the given pair of images.

So we train a Siamese Neural Network on various pairs of images which may contain two signatures from a person or two different signatures. For a pair in which both the signatures belong to the same person, we assign a label of 1 and for other cases, we assign a label of 0. It could be thought of as a binary classification problem where we have two classes “similar” and “not similar”.

Refer to these blogs to create a Siamese CNN ( the one with convolutional layers as inputs to the model are images ),

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