ew 18: e37

Research Article

A Survey of Biometric Recognition Using Deep Learning

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  • @ARTICLE{10.4108/eai.27-10-2020.166775,
        author={Haider Mehraj and Ajaz Hussain Mir},
        title={A  Survey  of  Biometric  Recognition  Using  Deep  Learning},
        journal={EAI Endorsed Transactions on Energy Web: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={EW},
        year={2020},
        month={10},
        keywords={Intelligent Systems, Unimodal Biometrics, Multimodal Biometrics, Deep Learning, and Transfer Learning},
        doi={10.4108/eai.27-10-2020.166775}
    }
    
  • Haider Mehraj
    Ajaz Hussain Mir
    Year: 2020
    A Survey of Biometric Recognition Using Deep Learning
    EW
    EAI
    DOI: 10.4108/eai.27-10-2020.166775
Haider Mehraj1,*, Ajaz Hussain Mir1
  • 1: Department of Electronics and Communication Engineering, National Institute of Technology Srinagar, Srinagar, J&K, India-19006
*Contact email: haider_50phd2015@nitsri.net

Abstract

Biometrics is a technique used to define, assess, and quantify a person's physical and behavioral property. In recent history, deep learning has shown impressive progress in several places, including computer vision and natural language processing for supervised learning. Since biometrics deals with a person's traits, it mainly involves supervised learning and may exploit deep learning effectiveness in other similar fields. In this article, a survey of more than 60 promising biometric works using deep learning is provided, illustrating their strengths and potential in various applications. The paper starts with biometric basics, transfer learning in deep biometrics, an overview of convolutional neural networks, and then survey work. We address all the strategies and datasets used along with their accuracy. Further, some of the main challenges when utilizing these biometric recognition models and potential future avenues for research into this field are also addressed.