Siamese-TDNN — это легендарная архитектура сиамских нейросетей, созданная для сверхточной верификации подписей. Модель использует две идентичные подсети для сравнения признаков, что заложило фундамент для современных систем распознавания лиц и биометрии. Этот AI-алгоритм эффективно определяет сходство объектов, вычисляя «расстояние» между их цифровыми отпечатками.
This paper describes an algorithm for verification of signatures written on a pen-input tablet. The algorithm is based on a novel, artificial neural network, called a "Siamese" neural network. This network consists of two identical sub-networks joined at their outputs. During training the two sub-networks extract features from two signatures, while the joining neuron measures the distance between the two feature vectors. Verification consists of comparing an extracted feature vector with a stored feature vector for the signer. Signatures closer to this stored representation than a chosen threshold are accepted, all other signatures are rejected as forgeries.