Derin Öǧrenme Tabani İmza Tanima Uygulamasi

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

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

6 Atıf (Scopus)

Özet

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.

Tercüme edilen katkı başlığıSignature recognition application based on deep learning
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2017 25th Signal Processing and Communications Applications Conference, SIU 2017
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781509064946
DOI'lar
Yayın durumuYayınlandı - 27 Haz 2017
Etkinlik25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey
Süre: 15 May 201718 May 2017

Yayın serisi

Adı2017 25th Signal Processing and Communications Applications Conference, SIU 2017

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???event.eventtypes.event.conference???25th Signal Processing and Communications Applications Conference, SIU 2017
Ülke/BölgeTurkey
ŞehirAntalya
Periyot15/05/1718/05/17

Bibliyografik not

Publisher Copyright:
© 2017 IEEE.

Keywords

  • biometric
  • convolutional artificial neural network
  • deep learning
  • signature recognition

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