An electronic contract handwritten signature authentication method based on twin neural networks
A handwritten signature, neural network technology, applied in biological neural network models, neural learning methods, neural architectures, etc., to ensure legal validity, save signing costs, and reduce losses.
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[0045] like figure 1 As shown, the principle of the twin neural network is: the twin neural network model is used to measure the similarity of two inputs, the twin neural network has two inputs Input1 and Input2, and the two inputs are respectively input into two neural networks Network1 and Network2, The two neural networks share the weight Weights, and map their respective inputs to a new space to form a representation of the input in the new space. Through the calculation of the loss function Loss Function, the similarity between two inputs is evaluated, that is, the distance.
[0046] like figure 2 As shown, the present embodiment provides a method for identifying a handwritten signature of an electronic contract based on a twin neural network, including the following steps:
[0047] S1: In the real-name authentication link, carry out several user handwritten signatures, and save several handwritten signatures as image files to form a training set;
[0048] S2: Randoml...
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