* Equal Contribution


  1. Towards Explainable Computer Vision Methods via Uncertainty Activation Map
    Seungyoun Shin, Wonho BaeJunhyug Noh, and Sungjoon Choi
    Asian Conference on Pattern Recognition (ACPR), 2023
  2. Robust Detection for Autonomous Elevator Boarding Using a Mobile Manipulator
    Seungyoun Shin, Joon Hyung Lee, Junhyug Noh, and Sungjoon Choi
    Asian Conference on Pattern Recognition (ACPR), 2023
  3. Predicting Outcomes of Continuous Renal Replacement Therapy Using Body Composition Monitoring: A Deep-Learning Approach
    Kyung Don Yoo*, Junhyug Noh*Wonho Bae, Jung Nam An, Hyung Jung Oh, Harin Rhee, Eun Young Seong, Seon Ha Baek, Shin Young Ahn, Jang-Hee Cho, and  others
    Scientific Reports, 2023


  1. Object Discovery via Contrastive Learning for Weakly Supervised Object Detection
    European Conference on Computer Vision (ECCV), 2022
  2. One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model
    Wonho BaeJunhyug Noh, Milad Jalali Asadabadi, and Danica J. Sutherland
    International Joint Conference on Artificial Intelligence (IJCAI), 2022
  3. Tackling the Challenges in Scene Graph Generation With Local-to-Global Interactions
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022


  1. What and When to Look?: Temporal Span Proposal Network for Video Relation Detection
    arXiv preprint, 2021
  2. Revisiting Dropout: Escaping Pressure for Training Neural Networks with Multiple Costs
    Sangmin WooKangil KimJunhyug Noh, Jong-Hun Shin, and Seung-Hoon Na
    Electronics, 2021
  3. Line Chart Understanding with Convolutional Neural Network
    Chanyoung Sohn, Heejong Choi, Kangil Kim, Jinwook Park, and Junhyug Noh
    Electronics, 2021


  1. Recalibration and Validation of the Charlson Comorbidity Index in an Asian Population: the National Health Insurance Service-National Sample Cohort Study
    Jae Shin Choi, Myoung-Hee Kim, Yong Chul Kim, Youn-Hee Lim, Hyun Joo Bae, Dong Ki Kim, Jae Yoon Park, Junhyug Noh, and Jung Pyo Lee
    Scientific Reports, 2020
  2. Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea
    Junhyug Noh*, Kyung Don Yoo*, Wonho Bae, Jong Soo Lee, Kangil Kim, Jang-Hee Cho, Hajeong Lee, Dong Ki Kim, Chun Soo Lim, Shin-Wook Kang, and  others
    Scientific reports, 2020
  3. Rethinking Class Activation Mapping for Weakly Supervised Object Localization
    European Conference on Computer Vision (ECCV), 2020


  1. Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection
    Junhyug NohWonho Bae, Wonhee Lee, Jinhwan Seo, and Gunhee Kim
    IEEE International Conference on Computer Vision (ICCV), 2019


  1. Stable Forecasting of Environmental Time Series via Long Short Term Memory Recurrent Neural Network
    Kangil Kim, Dong-Kyun Kim, Junhyug Noh, and Minhyeok Kim
    IEEE Access, 2018
  2. Conflict Relaxation of Activation-Based Regularization for Neural Network
    Kangil KimJunhyug Noh, Dong-Kyun Kim, and Minhyeok Kim
    IEEE Access, 2018
  3. Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018


  1. A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study
    Kyung Don Yoo*, Junhyug Noh*, Hajeong Lee, Dong Ki Kim, Chun Soo Lim, Young Hoon Kim, Jung Pyo Lee, Gunhee Kim, and Yon Su Kim
    Scientific reports, 2017


  1. Superior Outcomes of Kidney Transplantation Compared with Dialysis: An Optimal Matched Analysis of a National Population-based Cohort Study between 2005 and 2008 in Korea
    Kyung Don Yoo, Clara Tammy Kim, Myoung-Hee Kim, Junhyug NohGunhee Kim, Ho Kim, Jung Nam An, Jae Yoon Park, Hyunjeong Cho, Kyoung Hoon Kim, and  others
    Medicine, 2016


  1. Machine Learning Models and Statistical Measures for Predicting the Progression of IgA Nephropathy
    Junhyug Noh, Dharani Punithan, Hajeong Lee, JungPyo Lee, YonSu Kim, DongKi Kim, and Robert Ian McKay
    International Journal of Software Engineering and Knowledge Engineering, 2015


  1. Predicting the Progression of IgA Nephropathy using Machine Learning Methods
    Junhyug Noh, Dharani Punithan, Hajeong Lee, Jung Pyo Lee, Yon Su Kim, Dong Ki Kim, and Robert Ian McKay
    International Conference on Bioinspired Information and Communications Technologies, 2014


  1. Estimating Multiple Evoked Emotions from Videos
    Wonhee Choe, Hyo-Sun Chun, Junhyug Noh, Seong-Deok Lee, and Byoung-Tak Zhang
    Annual Meeting of the Cognitive Science Society (CogSci), 2013