DNA Recognition Using Novel Deep Learning Model


  • Musab Tahseen Salahaldeen Al-Kaltakchi Mustansiriyah University, Department of Electrical Engineering, College of Engineering, Mustansiriyah University, Baghdad, Iraq; http://orcid.org/0000-0001-5542-9144
  • Hasan A. Abdulla Technical Engineering College of Mosul, Northern Technical University, Iraq.
  • Raid Rafi Omar Al-Nima Technical Engineering College of Mosul, Northern Technical University, Iraq. http://orcid.org/0000-0002-9673-453X


DNA, a significant physiological biometric, is present
in all human cells like hair, blood, and skin. This research
introduces a new approach called the Deep DNA Learning
Network (DDLN) for person identification based on their DNA.
This novel Machine Learning model is designed to gather
DNA chromosomes from an individual’s parents. The model’s
flexibility allows it to expand or contract and has the capability to
determine one or both parents of an individual using the provided
chromosomes. Notably, the DDLN model offers quick training
in comparison to traditional deep learning methods. The study
employs two real datasets from Iraq: the Real Iraqi Dataset for
Kurds (RIDK) and the Real Iraqi Dataset for Arabs (RIDA). The
outcomes demonstrate that the proposed DDLN model achieves
an Equal Error Rate (EER) of 0 for both datasets, indicating
highly accurate performance.

Author Biographies

Musab Tahseen Salahaldeen Al-Kaltakchi, Mustansiriyah University, Department of Electrical Engineering, College of Engineering, Mustansiriyah University, Baghdad, Iraq;

Dr. Musab T. S. Al-Kaltakchi is a lecturer in the Electrical Engineering Department, Mustansiriyah University, Baghdad-Iraq. He obtained his BSc in Electrical Engineering in 1996 and obtained his MSc in Communication and Electronics in 2004 from Mustansiriyah University. He was awarded a PhD degree in Electrical Engineering/ Digital Signal Processing from Newcastle University, UK in 2018. He is a member of the Institute of Electrical and Electronic Engineering (IEEE) and also in the Institute of Engineering and Technology (IET). His research interests include Speaker identification and verification, Speech and audio signal processing, Machine learning, Artificial intelligence, Pattern recognition, and Biometrics. He can be contacted at Email: musab.tahseen@gmail.com & at Email: m.t.s.al_kaltakchi@uomustansiriyah.edu.iq.

Hasan A. Abdulla, Technical Engineering College of Mosul, Northern Technical University, Iraq.

Technical Engineering College of Mosul, Northern Technical University, Iraq. 



Raid Rafi Omar Al-Nima, Technical Engineering College of Mosul, Northern Technical University, Iraq.

Technical Engineering College of Mosul, Northern Technical University, Iraq. 




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Digital Signal Processing