| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1354 | 2023 |
| Fast autoaugment S Lim, I Kim, T Kim, C Kim, S Kim Advances in neural information processing systems 32, 2019 | 792 | 2019 |
| Edge-labeling graph neural network for few-shot learning J Kim, T Kim, S Kim, CD Yoo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 628 | 2019 |
| Bayesian model-agnostic meta-learning J Yoon, T Kim, O Dia, S Kim, Y Bengio, S Ahn Advances in neural information processing systems 31, 2018 | 502 | 2018 |
| A comparative study of modern inference techniques for structured discrete energy minimization problems JH Kappes, B Andres, FA Hamprecht, C Schnörr, S Nowozin, D Batra, ... International Journal of Computer Vision 115, 155-184, 2015 | 244 | 2015 |
| A comparative study of modern inference techniques for discrete energy minimization problems J Kappes, B Andres, F Hamprecht, C Schnorr, S Nowozin, D Batra, S Kim, ... Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 224 | 2013 |
| Higher-order correlation clustering for image segmentation S Kim, S Nowozin, P Kohli, C Yoo Advances in neural information processing systems 24, 2011 | 181 | 2011 |
| Bayesian model-agnostic meta-learning T Kim, J Yoon, O Dia, S Kim, Y Bengio, S Ahn arXiv preprint arXiv:1806.03836, 2018 | 160 | 2018 |
| Image segmentation usinghigher-order correlation clustering S Kim, CD Yoo, S Nowozin, P Kohli IEEE transactions on pattern analysis and machine intelligence 36 (9), 1761-1774, 2014 | 149 | 2014 |
| Spatially consistent representation learning B Roh, W Shin, I Kim, S Kim Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 116 | 2021 |
| Electronic device generating notification based on context data in response to speech phrase from user S Yun, T Kim, SW Kim, H Kim US Patent 9,946,862, 2018 | 114 | 2018 |
| Learning loss for test-time augmentation I Kim, Y Kim, S Kim Advances in neural information processing systems 33, 4163-4174, 2020 | 110 | 2020 |
| Scalable neural architecture search for 3d medical image segmentation S Kim, I Kim, S Lim, W Baek, C Kim, H Cho, B Yoon, T Kim Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 93 | 2019 |
| torchgpipe: On-the-fly pipeline parallelism for training giant models C Kim, H Lee, M Jeong, W Baek, B Yoon, I Kim, S Lim, S Kim arXiv preprint arXiv:2004.09910, 2020 | 57 | 2020 |
| Contrastive regularization for semi-supervised learning D Lee, S Kim, I Kim, Y Cheon, M Cho, WS Han Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 55 | 2022 |
| Pairwise boosted audio fingerprint D Jang, CD Yoo, S Lee, S Kim, T Kalker IEEE transactions on information forensics and security 4 (4), 995-1004, 2009 | 53 | 2009 |
| Wearable sensor activity analysis using semi-Markov models with a grammar O Thomas, P Sunehag, G Dror, S Yun, S Kim, M Robards, A Smola, ... Pervasive and Mobile Computing 6 (3), 342-350, 2010 | 47 | 2010 |
| Spatially attentive output layer for image classification I Kim, W Baek, S Kim Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 38 | 2020 |
| Task-specific image partitioning S Kim, S Nowozin, P Kohli, CD Yoo IEEE Transactions on Image Processing 22 (2), 488-500, 2012 | 32 | 2012 |
| Boosted binary audio fingerprint based on spectral subband moments S Kim, CD Yoo 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 27 | 2007 |
Taesup KimAssistant Professor, Seoul National UniversityVerified email at snu.ac.kr