Introduction



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 paper accepted for spotlight presentation at NIPS 2018.
    Yunho Jeon and Junmo Kim, "Constructing Fast Network through Deconstruction of Convolution,” Advances in Neural Information Processing Systems (NIPS) 2018.
    Posted Sep 7, 2018, 5:44 AM by 윤주승
  • We have two papers accepted for BMVC 2018.
    1. Byungju Kim, Junho Yim and Junmo Kim, "Highway Driving Dataset for Semantic Video Segmentation"

    2. Donggyu Joo, Junho Yim and Junmo Kim, "Unconstrained Control of Feature Map Size Using Non-integer Strided Sampling"
    Posted Sep 7, 2018, 5:43 AM by 윤주승
  • We have a publication accepted for UAI 2018.
    Sihyeon Seong, Yegang Lee, Youngwook Kee, Dongyoon Han and Junmo Kim, "Towards Flatter Loss Surface via Nonmonotonic Learning Rate Scheduling", The Conference on Uncertainty in Artificial Intelligence (UAI), 2018 - oral paper
    Posted May 18, 2018, 1:55 AM by 윤주승
  • We have two publications accepted.
    1. IEEE Transactions on Affective Computing.

    Woo-han Yun, Dongjin Lee, Chankyu Park, Jaehong Kim, and Junmo Kim, “Automatic Recognition of Children Engagement from Facial Video using Convolutional Neural Networks,” to appear in IEEE Transactions on Affective Computing.

    2. Sensors

    Sohyun Kim, Gwang-Il Jang, Sungho Kim, and Junmo Kim, “Computationally efficient automatic coast mode target tracking based 
    on occlusion aware in infrared images,” to appear in Sensors.
    Posted May 2, 2018, 5:41 AM by 윤주승
  • We have a publication accepted for IEEE Signal Processing Letters.
    ByungIn Yoo, Youngjun Kwak, Youngsung Kim, Changkyu Choi, and Junmo Kim, "Deep Facial Age Estimation using Conditional Multitask Learning with Weak Label Expansion," to appear in IEEE Signal Processing Letters.
    Posted Mar 28, 2018, 8:43 AM by 윤주승
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