GDL

Journal from gdlhub / 2021-09-06 17:06:40
Oleh : Lubab H. Albak, Raid Rafi Omar Al-Nima, Arwa Hamid Salih, Telkomnika
Dibuat : 2021-09-06, dengan 0 file

Keyword : deep learning, palm print, pattern recognition
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/16573
Sumber pengambilan dokumen : Web

In this paper, we consider a palm print characteristic which has taken wide attentions in recent studies. We focused on palm print verification problem by designing a deep network called a palm convolutional neural network (PCNN). This network is adapted to deal with two-dimensional palm print images. It is carefully designed and implemented for palm print data. Palm prints from the Hong Kong Polytechnic University Contact-free (PolyUC) 3D/2D hand images dataset are applied and evaluated. The results have reached the accuracy of 97.67%, this performance is superior and it shows that our proposed method is efficient.

Deskripsi Alternatif :

In this paper, we consider a palm print characteristic which has taken wide attentions in recent studies. We focused on palm print verification problem by designing a deep network called a palm convolutional neural network (PCNN). This network is adapted to deal with two-dimensional palm print images. It is carefully designed and implemented for palm print data. Palm prints from the Hong Kong Polytechnic University Contact-free (PolyUC) 3D/2D hand images dataset are applied and evaluated. The results have reached the accuracy of 97.67%, this performance is superior and it shows that our proposed method is efficient.

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