Seungjoon Yang

Seungjoon Yang

Ulsan National Institute of Science and Technology

Associate Professor

School of Electrical Engineering

Research Area

  • #Artificial intelligence
  • #Computer science
  • #Computer vision
  • #Pixel
  • #Pattern recognition
  • #Mathematics
  • #Optics
  • #Lens (optics)
  • #Salience (neuroscience)
  • #Divide and conquer algorithms

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Related papers to
‘ Artificial intelligence ‘ : 6

  • Deep belief network based statistical feature learning for fingerprint liveness detection

    2016/07

    2.0 Impact Factor

    34 citations

    Soowoong Kim, Bogun Park, Bong Seop Song, Seungjoon Yang

    DOI : 10.1016/J.PATREC.2016.03.015

    • #Computer science
    • #Artificial intelligence
    • #Pattern recognition
    • #Machine learning
    • #Discriminative model
    • #Fingerprint
    • #Feature learning
    • #Liveness
    • #Deep learning
    • #Fingerprint recognition
    • #Deep belief network
    • #Restricted Boltzmann machine

All papers authored by
‘ Seungjoon Yang ’ : 8

  • Deep belief network based statistical feature learning for fingerprint liveness detection

    2016/07
    PATTERN RECOGNITION LETTERS

    2.0 Impact Factor

    34 citations

    Soowoong Kim, Bogun Park, Bong Seop Song, Seungjoon Yang

    DOI : 10.1016/J.PATREC.2016.03.015

    • #Computer science
    • #Artificial intelligence
    • #Pattern recognition
    • #Machine learning
    • #Discriminative model
    • #Fingerprint
    • #Feature learning
    • #Liveness
    • #Deep learning
    • #Fingerprint recognition
    • #Deep belief network
    • #Restricted Boltzmann machine

Related papers to
‘ Artificial intelligence ‘ : 6

  • Deep belief network based statistical feature learning for fingerprint liveness detection

    2016/07
    PATTERN RECOGNITION LETTERS

    2.0 Impact Factor

    34 citations

    Soowoong Kim, Bogun Park, Bong Seop Song, Seungjoon Yang

    DOI : 10.1016/J.PATREC.2016.03.015

    • #Computer science
    • #Artificial intelligence
    • #Pattern recognition
    • #Machine learning
    • #Discriminative model
    • #Fingerprint
    • #Feature learning
    • #Liveness
    • #Deep learning
    • #Fingerprint recognition
    • #Deep belief network
    • #Restricted Boltzmann machine
  • Saliency-based initialisation of Gaussian mixture models for fully-automatic object segmentation

    2017/11
    ELECTRONICS LETTERS

    1.2 Impact Factor

    3 citations

    Garam Kim, Seungjoon Yang, Jae-Young Sim

    DOI : 10.1049/EL.2017.3877

    • #Computer science
    • #Artificial intelligence
    • #Computer vision
    • #Pattern recognition
    • #Matrix (mathematics)
    • #Pixel
    • #Segmentation
    • #Salient
    • #Mixture model
    • #Salience (neuroscience)
    • #Active appearance model
    • #Covariance

Get access to
Contact information

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All papers authored by
‘ Seungjoon Yang ’ : 8

  • Deep belief network based statistical feature learning for fingerprint liveness detection

    2016/07
    PATTERN RECOGNITION LETTERS

    2.0 Impact Factor

    34 citations

    Soowoong Kim, Bogun Park, Bong Seop Song, Seungjoon Yang

    DOI : 10.1016/J.PATREC.2016.03.015

    • #Computer science
    • #Artificial intelligence
    • #Pattern recognition
    • #Machine learning
    • #Discriminative model
    • #Fingerprint
    • #Feature learning
    • #Liveness
    • #Deep learning
    • #Fingerprint recognition
    • #Deep belief network
    • #Restricted Boltzmann machine
  • Parallel Block Sequential Closed-Form Matting With Fan-Shaped Partitions

    2018/02
    IEEE TRANSACTIONS ON IMAGE PROCESSING

    6.8 Impact Factor

    4 citations

    Yongsik Lee, Seungjoon Yang

    DOI : 10.1109/TIP.2017.2765827

    • #Computer science
    • #Algorithm
    • #Scalability
    • #Computational complexity theory
    • #Solver
    • #System of linear equations
    • #Linear equation
    • #Benchmark (computing)
    • #Divide and conquer algorithms
    • #Image segmentation

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