Taesup Moon (문태섭)
Taesup Moon (문태섭)
Associate Professor, Department of Electrical and Computer Engineering, Seoul National University
Verified email at - Homepage
Cited by
Cited by
Human detection and activity classification based on micro-Doppler signatures using deep convolutional neural networks
Y Kim, T Moon
IEEE geoscience and remote sensing letters 13 (1), 8-12, 2015
An unbiased offline evaluation of contextual bandit algorithms with generalized linear models
L Li, W Chu, J Langford, T Moon, X Wang
Proceedings of the Workshop on On-line Trading of Exploration and …, 2012
Fooling neural network interpretations via adversarial model manipulation
J Heo, S Joo, T Moon
Advances in Neural Information Processing Systems 32, 2019
Skip-connected 3D DenseNet for volumetric infant brain MRI segmentation
TD Bui, J Shin, T Moon
Biomedical Signal Processing and Control 54, 101613, 2019
Micro-Doppler based classification of human aquatic activities via transfer learning of convolutional neural networks
J Park, RJ Javier, T Moon, Y Kim
Sensors 16 (12), 1990, 2016
Learning to model relatedness for news recommendation
Y Lv, T Moon, P Kolari, Z Zheng, X Wang, Y Chang
Proceedings of the 20th international conference on World wide web, 57-66, 2011
Rnndrop: A novel dropout for rnns in asr
T Moon, H Choi, H Lee, I Song
2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU …, 2015
Uncertainty-based continual learning with adaptive regularization
H Ahn, S Cha, D Lee, T Moon
Advances in neural information processing systems 32, 2019
Ss-il: Separated softmax for incremental learning
H Ahn, J Kwak, S Lim, H Bang, H Kim, T Moon
Proceedings of the IEEE/CVF International conference on computer vision, 844-853, 2021
Toward a unified framework for interpreting machine-learning models in neuroimaging
L Kohoutová, J Heo, S Cha, S Lee, T Moon, TD Wager, CW Woo
Nature protocols 15 (4), 1399-1435, 2020
Subtask gated networks for non-intrusive load monitoring
C Shin, S Joo, J Yim, H Lee, T Moon, W Rhee
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 1150-1157, 2019
Estimating PM2. 5 concentration of the conterminous United States via interpretable convolutional neural networks
Y Park, B Kwon, J Heo, X Hu, Y Liu, T Moon
Environmental Pollution 256, 113395, 2020
An online learning framework for refining recency search results with user click feedback
T Moon, W Chu, L Li, Z Zheng, Y Chang
ACM Transactions on Information Systems (TOIS) 30 (4), 1-28, 2012
DUDE-Seq: fast, flexible, and robust denoising for targeted amplicon sequencing
B Lee, T Moon, S Yoon, T Weissman
PloS one 12 (7), e0181463, 2017
Continual learning with node-importance based adaptive group sparse regularization
S Jung, H Ahn, S Cha, T Moon
Advances in Neural Information Processing Systems 33, 3647-3658, 2020
Intervalrank: isotonic regression with listwise and pairwise constraints
T Moon, A Smola, Y Chang, Z Zheng
Proceedings of the third ACM international conference on Web search and data …, 2010
Fully convolutional pixel adaptive image denoiser
S Cha, T Moon
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Fair feature distillation for visual recognition
S Jung, D Lee, T Park, T Moon
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
Universal fir mmse filtering
T Moon, T Weissman
IEEE Transactions on Signal Processing 57 (3), 1068-1083, 2008
CPR: classifier-projection regularization for continual learning
S Cha, H Hsu, T Hwang, FP Calmon, T Moon
arXiv preprint arXiv:2006.07326, 2020
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