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- W2395010941 abstract "Handwritten signatures are the most natural way of authenticating a person’s identity. An offline signature verification system generally consists of four components: data acquisition, pre- processing, feature extraction, recognition and verification. This paper presents a method for verifying handwritten signature by using NN architecture. In proposed methods the multi-layer perceptron (MLP), modular neural networks with generalized feed-forward networks and Self Organizing Map groups (SOM) neural network with competitive learning will be considered. Self Organizing Map groups the input data into clusters which are commonly used for unsupervised training. After recognition and verification of input data FRR, FAR and TER is calculated." @default.
- W2395010941 created "2016-06-24" @default.
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- W2395010941 date "2013-01-01" @default.
- W2395010941 modified "2023-09-27" @default.
- W2395010941 title "Neural Network Based Offline Signature Recognition and Verification System" @default.
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