How Siamese Neural Networks Work With Image Processing
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Frequently Asked Questions
How does a Siamese network work?
Siamese networks are made up of two identical neural networks, each of which takes one of the two input images. The last layers of the two networks are then sent into a contrastive loss function which computes the degree of similarity between the two images.
What is a Siamese network used for?
Siamese networks are used to apply similarity learning, i.e., to find where there’s a similarity of patterns and structures in two images.
What is a Siamese convolutional neural network?
A Siamese neural network, also known as a twin neural network, is a type of artificial neural network that employs the same weights to compute equivalent output vectors from two distinct input vectors simultaneously.