Publications

2023

1. Towards Explainable Computer Vision Methods via Uncertainty Activation Map

   Seungyoun Shin, Wonho Bae, Junhyug Noh, and Sungjoon Choi

   Asian Conference on Pattern Recognition (ACPR), 2023

   Bib

   @article{shin:2023:uam,
     title = {Towards Explainable Computer Vision Methods via Uncertainty Activation Map},
     author = {Shin, Seungyoun and Bae, Wonho and Noh, Junhyug and Choi, Sungjoon},
     journal = {Asian Conference on Pattern Recognition (ACPR)},
     pages = {1--14},
     year = {2023},
     organization = {Springer}
   }

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

   Bib

   @article{shin:2023:elevator,
     title = {Robust Detection for Autonomous Elevator Boarding Using a Mobile Manipulator},
     author = {Shin, Seungyoun and Lee, Joon Hyung and Noh, Junhyug and Choi, Sungjoon},
     journal = {Asian Conference on Pattern Recognition (ACPR)},
     pages = {15--28},
     year = {2023},
     organization = {Springer}
   }

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

   Bib

   @article{yoo:2023:crrt,
     title = {Predicting Outcomes of Continuous Renal Replacement Therapy Using Body Composition Monitoring: A Deep-Learning Approach},
     author = {Yoo*, Kyung Don and Noh*, Junhyug and Bae, Wonho and An, Jung Nam and Oh, Hyung Jung and Rhee, Harin and Seong, Eun Young and Baek, Seon Ha and Ahn, Shin Young and Cho, Jang-Hee and others},
     journal = {Scientific Reports},
     volume = {13},
     number = {1},
     pages = {4605},
     year = {2023},
     publisher = {Nature Publishing Group UK London}
   }

2022

1. Object Discovery via Contrastive Learning for Weakly Supervised Object Detection

   Jinhwan Seo, Wonho Bae, Danica J. Sutherland, Junhyug Noh*, and Daijin Kim*

   European Conference on Computer Vision (ECCV), 2022

   arXiv Bib

   @article{seo:2022:wsod,
     title = {Object Discovery via Contrastive Learning for Weakly Supervised Object Detection},
     author = {Seo, Jinhwan and Bae, Wonho and Sutherland, Danica J. and Noh*, Junhyug and Kim*, Daijin},
     journal = {European Conference on Computer Vision (ECCV)},
     pages = {312--329},
     year = {2022},
     organization = {Springer}
   }

2. One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model

   Wonho Bae, Junhyug Noh, Milad Jalali Asadabadi, and Danica J. Sutherland

   International Joint Conference on Artificial Intelligence (IJCAI), 2022

   arXiv Bib

   @article{bae:2022:swsss,
     title = {One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model},
     author = {Bae, Wonho and Noh, Junhyug and Asadabadi, Milad Jalali and Sutherland, Danica J.},
     journal = {International Joint Conference on Artificial Intelligence (IJCAI)},
     pages = {2805--2811},
     year = {2022}
   }

3. Tackling the Challenges in Scene Graph Generation With Local-to-Global Interactions

   Sangmin Woo, Junhyug Noh, and Kangil Kim

   IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022

   arXiv Bib

   @article{woo:2022:tackling,
     title = {Tackling the Challenges in Scene Graph Generation With Local-to-Global Interactions},
     author = {Woo, Sangmin and Noh, Junhyug and Kim, Kangil},
     journal = {IEEE Transactions on Neural Networks and Learning Systems (TNNLS)},
     year = {2022},
     publisher = {IEEE}
   }

2021

1. What and When to Look?: Temporal Span Proposal Network for Video Relation Detection

   Sangmin Woo, Junhyug Noh, and Kangil Kim

   arXiv preprint, 2021

   arXiv Bib

   @article{woo:2021:whatandwhen,
     title = {What and When to Look?: Temporal Span Proposal Network for Video Relation Detection},
     author = {Woo, Sangmin and Noh, Junhyug and Kim, Kangil},
     journal = {arXiv preprint},
     year = {2021}
   }

2. Revisiting Dropout: Escaping Pressure for Training Neural Networks with Multiple Costs

   Sangmin Woo, Kangil Kim, Junhyug Noh, Jong-Hun Shin, and Seung-Hoon Na

   Electronics, 2021

   Bib

   @article{woo:2021:revisiting,
     title = {Revisiting Dropout: Escaping Pressure for Training Neural Networks with Multiple Costs},
     author = {Woo, Sangmin and Kim, Kangil and Noh, Junhyug and Shin, Jong-Hun and Na, Seung-Hoon},
     journal = {Electronics},
     volume = {10},
     number = {9},
     pages = {989},
     year = {2021}
   }

3. Line Chart Understanding with Convolutional Neural Network

   Chanyoung Sohn, Heejong Choi, Kangil Kim, Jinwook Park, and Junhyug Noh

   Electronics, 2021

   Bib

   @article{sohn:2021:line,
     title = {Line Chart Understanding with Convolutional Neural Network},
     author = {Sohn, Chanyoung and Choi, Heejong and Kim, Kangil and Park, Jinwook and Noh, Junhyug},
     journal = {Electronics},
     volume = {10},
     number = {6},
     pages = {749},
     year = {2021}
   }

2020

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

   Bib

   @article{choi:2020:recalibration,
     title = {Recalibration and Validation of the Charlson Comorbidity Index in an Asian Population: the National Health Insurance Service-National Sample Cohort Study},
     author = {Choi, Jae Shin and Kim, Myoung-Hee and Kim, Yong Chul and Lim, Youn-Hee and Bae, Hyun Joo and Kim, Dong Ki and Park, Jae Yoon and Noh, Junhyug and Lee, Jung Pyo},
     journal = {Scientific Reports},
     volume = {10},
     number = {1},
     pages = {13715},
     year = {2020},
     publisher = {Nature Publishing Group UK London}
   }

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

   Bib

   @article{noh:2020:peritoneal,
     title = {Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea},
     author = {Noh*, Junhyug and Yoo*, Kyung Don and Bae, Wonho and Lee, Jong Soo and Kim, Kangil and Cho, Jang-Hee and Lee, Hajeong and Kim, Dong Ki and Lim, Chun Soo and Kang, Shin-Wook and others},
     journal = {Scientific reports},
     volume = {10},
     number = {1},
     pages = {7470},
     year = {2020},
     publisher = {Nature Publishing Group UK London}
   }

3. Rethinking Class Activation Mapping for Weakly Supervised Object Localization

   Wonho Bae*, Junhyug Noh*, and Gunhee Kim

   European Conference on Computer Vision (ECCV), 2020

   Bib

   @article{bae:2020:rethinking,
     title = {Rethinking Class Activation Mapping for Weakly Supervised Object Localization},
     author = {Bae*, Wonho and Noh*, Junhyug and Kim, Gunhee},
     journal = {European Conference on Computer Vision (ECCV)},
     pages = {618--634},
     year = {2020}
   }

2019

1. Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection

   Junhyug Noh, Wonho Bae, Wonhee Lee, Jinhwan Seo, and Gunhee Kim

   IEEE International Conference on Computer Vision (ICCV), 2019

   Bib

   @article{noh:2019:better,
     title = {Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection},
     author = {Noh, Junhyug and Bae, Wonho and Lee, Wonhee and Seo, Jinhwan and Kim, Gunhee},
     journal = {IEEE International Conference on Computer Vision (ICCV)},
     pages = {9725--9734},
     year = {2019}
   }

2018

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

   Bib

   @article{kim:2018:stable,
     title = {Stable Forecasting of Environmental Time Series via Long Short Term Memory Recurrent Neural Network},
     author = {Kim, Kangil and Kim, Dong-Kyun and Noh, Junhyug and Kim, Minhyeok},
     journal = {IEEE Access},
     volume = {6},
     pages = {75216--75228},
     year = {2018},
     publisher = {IEEE}
   }

2. Conflict Relaxation of Activation-Based Regularization for Neural Network

   Kangil Kim, Junhyug Noh, Dong-Kyun Kim, and Minhyeok Kim

   IEEE Access, 2018

   Bib

   @article{kim:2018:conflict,
     title = {Conflict Relaxation of Activation-Based Regularization for Neural Network},
     author = {Kim, Kangil and Noh, Junhyug and Kim, Dong-Kyun and Kim, Minhyeok},
     journal = {IEEE Access},
     volume = {6},
     pages = {52510--52518},
     year = {2018},
     publisher = {IEEE}
   }

3. Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors

   Junhyug Noh, Soochan Lee, Beomsu Kim, and Gunhee Kim

   IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018

   Bib

   @article{noh:2018:improving,
     title = {Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors},
     author = {Noh, Junhyug and Lee, Soochan and Kim, Beomsu and Kim, Gunhee},
     journal = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
     pages = {966--974},
     year = {2018}
   }

2017

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

   Bib

   @article{yoo:2017:kidneytransplant,
     title = {A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study},
     author = {Yoo*, Kyung Don and Noh*, Junhyug and Lee, Hajeong and Kim, Dong Ki and Lim, Chun Soo and Kim, Young Hoon and Lee, Jung Pyo and Kim, Gunhee and Kim, Yon Su},
     journal = {Scientific reports},
     volume = {7},
     number = {1},
     pages = {8904},
     year = {2017},
     publisher = {Nature Publishing Group UK London}
   }

2016

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 Noh, Gunhee Kim, Ho Kim, Jung Nam An, Jae Yoon Park, Hyunjeong Cho, Kyoung Hoon Kim, and  others

   Medicine, 2016

   Bib

   @article{yoo:2016:superior,
     title = {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},
     author = {Yoo, Kyung Don and Kim, Clara Tammy and Kim, Myoung-Hee and Noh, Junhyug and Kim, Gunhee and Kim, Ho and An, Jung Nam and Park, Jae Yoon and Cho, Hyunjeong and Kim, Kyoung Hoon and others},
     journal = {Medicine},
     volume = {95},
     number = {33},
     year = {2016},
     publisher = {Wolters Kluwer Health}
   }

2015

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

   Bib

   @article{noh:2015:igan2,
     title = {Machine Learning Models and Statistical Measures for Predicting the Progression of IgA Nephropathy},
     author = {Noh, Junhyug and Punithan, Dharani and Lee, Hajeong and Lee, JungPyo and Kim, YonSu and Kim, DongKi and McKay, Robert Ian},
     journal = {International Journal of Software Engineering and Knowledge Engineering},
     volume = {25},
     number = {05},
     pages = {829--849},
     year = {2015}
   }

2014

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

   Bib

   @article{noh:2014:igan,
     title = {Predicting the Progression of IgA Nephropathy using Machine Learning Methods},
     author = {Noh, Junhyug and Punithan, Dharani and Lee, Hajeong and Lee, Jung Pyo and Kim, Yon Su and Kim, Dong Ki and McKay, Robert Ian},
     journal = {International Conference on Bioinspired Information and Communications Technologies},
     pages = {328--335},
     year = {2014}
   }

2013

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

   Bib

   @article{choe:2013:videoemotion,
     title = {Estimating Multiple Evoked Emotions from Videos},
     author = {Choe, Wonhee and Chun, Hyo-Sun and Noh, Junhyug and Lee, Seong-Deok and Zhang, Byoung-Tak},
     journal = {Annual Meeting of the Cognitive Science Society (CogSci)},
     volume = {35},
     number = {35},
     year = {2013}
   }