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文件名称:offline-signature-recognition
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- 上传时间:2016-01-05
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As signatures are widely accepted bio-metric for authentication and identification of a person because every person
has a distinct signature with its specific behavioral property, so it is very much necessary to prove the authenticity of signature
itself. There are various techniques to signature recognition with a lot of scope of research. In this paper off-line signature
recognition and verification system using Artificial Neural Network (ANN) is purposed. The purposed network based upon the
adaption of ANN to recognized signature to connected type pattern. The purpose ANN was trained with back propagation with
momentum and adaptive learning rate. A triple hidden layer ANN with 100 inputs 58.38.20 hidden neurons layers and 5 neurons
in output layers gives best results as compared with other networks. This paper represents a brief review on various approaches
used in signature verification systems.
has a distinct signature with its specific behavioral property, so it is very much necessary to prove the authenticity of signature
itself. There are various techniques to signature recognition with a lot of scope of research. In this paper off-line signature
recognition and verification system using Artificial Neural Network (ANN) is purposed. The purposed network based upon the
adaption of ANN to recognized signature to connected type pattern. The purpose ANN was trained with back propagation with
momentum and adaptive learning rate. A triple hidden layer ANN with 100 inputs 58.38.20 hidden neurons layers and 5 neurons
in output layers gives best results as compared with other networks. This paper represents a brief review on various approaches
used in signature verification systems.
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offline signature recognition.pdf
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