التفاصيل البيبلوغرافية
| العنوان: |
Automatic Signature Verifier Using Gaussian Gated Recurrent Unit Neural Network. |
| المؤلفون: |
Khan, Sameera1 (AUTHOR), Singh, Dileep Kumar2 (AUTHOR), Singh, Mahesh3 (AUTHOR), Mena, Desta Faltaso3 (AUTHOR) |
| المصدر: |
IET Biometrics (Wiley-Blackwell). 11/14/2023, Vol. 2023, p1-12. 12p. |
| مصطلحات موضوعية: |
*RECURRENT neural networks, *HANDWRITING recognition (Computer science), *BIOMETRIC identification |
| مستخلص: |
Handwritten signatures are one of the most extensively utilized biometrics used for authentication, and forgeries of this behavioral biometric are quite widespread. Biometric databases are also difficult to access for training purposes due to privacy issues. The efficiency of automated authentication systems has been severely harmed as a result of this. Verification of static handwritten signatures with high efficiency remains an open research problem to date. This paper proposes an innovative introselect median filter for preprocessing and a novel Gaussian gated recurrent unit neural network (2GRUNN) as a classifier for designing an automatic verifier for handwritten signatures. The proposed classifier has achieved an FPR of 1.82 and an FNR of 3.03. The efficacy of the proposed method has been compared with the various existing neural network-based verifiers. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |
Full Text Finder