The Statistical Inference and Information Theory Laboratory is directed by professor Junmo Kim since 2009. Our research focuses on development of theoretical methods which can be applied to image processing, computer vision, pattern recognition, and machine learning. For more information about our research topics, click here.

Recent Announcements

  • We have a publication accepted for AAAI 2018
    Heechul Jung, Jeongwoo Ju, Minju Jung and Junmo Kim, "Less-forgetful Learning in Deep Neural Networks for Domain Expansion in Image Classification", The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018
    Posted Nov 9, 2017, 1:05 AM by 윤주승
  • Prof. Junmo Kim will be serving as an Area Chair of CVPR 2018.

    Posted Oct 25, 2017, 7:20 AM by Jaeyoung Lee
  • Prof. Junmo Kim has been granted tenure and appointed as a tenured associate professor.

    Posted Oct 25, 2017, 7:19 AM by Jaeyoung Lee
  • We have a publication accepted for TPAMI 2017.
    Gayoung Lee, Yu-Wing Tai, and Junmo Kim, “ELD-Net: An efficient deep learning architecture for accurate saliency detection.”
    Posted Aug 6, 2017, 5:00 PM by Jaeyoung Lee
  • We have two publications accepted.
    1. SIAM Journal on Imaging Sciences

    Y. Kee, Y. Lee, M. Souiai, D. Cremers, and J. Kim, “Sequential Convex Programming
    for Computing Information-Theoretic Minimal Partitions: Nonconvex Nonsmooth
    Optimization,” to appear in SIAM Journal on Imaging Sciences.

    2.  Medical Physics

    H. Lee, H. Hong, D. C. Jung, S. Park, and J. Kim, “Differentiation of Fat-poor
    Angiomyolipoma from Clear Cell Renal Cell Carcinoma in Contrast-enhanced MDCT
    Images Using Quantitative Feature Classification,” to appear in Medical Physics.
    Posted Apr 9, 2017, 5:58 PM by Jaeyoung Lee
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