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Handwritten Signature Forgery Detection using Convolutional Neural Networks

机译:使用卷积神经网络的手写签名伪造探测

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摘要

Handwritten signatures are very important in our social and legal life for verification and authentication. A signature can be accepted only if it is from the intended person. The probability of two signatures made by the same person being the same is very less. Many properties of the signature may vary even when two signatures are made by the same person. So, detecting a forgery becomes a challenging task. In this paper, a solution based on Convolutional Neural Network (CNN) is presented where the model is trained with a dataset of signatures, and predictions are made as to whether a provided signature is genuine or forged.
机译:手写签名在我们的社会和法律生活中非常重要,用于验证和认证。只有当它来自预期的人时才可以接受签名。由同一个人制作的两个签名的可能性非常少。即使在同一个人制作两个签名时,签名的许多属性也可能有所不同。因此,检测伪造成为一个具有挑战性的任务。本文介绍了基于卷积神经网络(CNN)的解决方案,其中模型用签名数据集训练,并且对提供的签名是真实的或伪造的预测。

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