Derin Öǧrenme Tabani İmza Tanima Uygulamasi

Translated title of the contribution: Signature recognition application based on deep learning

Nurullah Calik*, Onur Can Kurban, Ali Riza Yilmaz, Lutfiye Durak Ata, Tulay Yildirim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Nowadays, with the increase of biometric studies, the diversity of biometric data increases and new methods are used in evaluation methods. Traditional biometrics, such as face, fingerprints, handpieces, now leave their place to a variety of biometrics, which contain characteristic information about more people and include movement information. In this study, the performance of the deep learning method based on convolutional neural network (CNN) is demonstrated on a nonlinear signature recognition problem. In this non-real-time signature recognition application, it has been tried to reduce the process load and memory requirement by using deep learning method. Two data sets with different participant numbers were created in the study. The performance and reliability of the system are examined by various ratios of training and testing data on these data sets.

Translated title of the contributionSignature recognition application based on deep learning
Original languageTurkish
Title of host publication2017 25th Signal Processing and Communications Applications Conference, SIU 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509064946
DOIs
Publication statusPublished - 27 Jun 2017
Event25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey
Duration: 15 May 201718 May 2017

Publication series

Name2017 25th Signal Processing and Communications Applications Conference, SIU 2017

Conference

Conference25th Signal Processing and Communications Applications Conference, SIU 2017
Country/TerritoryTurkey
CityAntalya
Period15/05/1718/05/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

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