| Adversarial dropout for supervised and semi-supervised learning S Park, JK Park, SJ Shin, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 84 | 2018 |
| What is wrong with scene text recognition model comparisons? dataset and model analysis J Baek, G Kim, J Lee, S Park, D Han, S Yun, SJ Oh, H Lee Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 83 | 2019 |
| Efficient extraction of domain specific sentiment lexicon with active learning S Park, W Lee, IC Moon Pattern Recognition Letters 56, 38-44, 2015 | 60 | 2015 |
| Identifying prescription patterns with a topic model of diseases and medications S Park, D Choi, M Kim, W Cha, C Kim, IC Moon Journal of biomedical informatics 75, 35-47, 2017 | 18 | 2017 |
| Diagnosis prediction via medical context attention networks using deep generative modeling W Lee, S Park, W Joo, IC Moon 2018 IEEE International Conference on Data Mining (ICDM), 1104-1109, 2018 | 12 | 2018 |
| Dirichlet variational autoencoder W Joo, W Lee, S Park, IC Moon Pattern Recognition 107, 107514, 2020 | 9 | 2020 |
| Modeling multiple fields of collective emotions with brownian agent-based model W Lee, S Park, IC Moon Proceedings of the 2014 international conference on Autonomous agents and …, 2014 | 6 | 2014 |
| Hierarchical context enabled recurrent neural network for recommendation K Song, M Ji, S Park, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4983-4991, 2019 | 5 | 2019 |
| Supervised dynamic topic models for associative topic extraction with a numerical time series S Park, W Lee, IC Moon Proceedings of the 2015 Workshop on Topic Models: Post-Processing and …, 2015 | 5 | 2015 |
| Associative topic models with numerical time series S Park, W Lee, IC Moon Information Processing & Management 51 (5), 737-755, 2015 | 5 | 2015 |
| On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention J Lee, S Park, J Baek, SJ Oh, S Kim, H Lee Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 3 | 2020 |
| Post-OCR parsing: building simple and robust parser via BIO tagging W Hwang, S Kim, M Seo, J Yim, S Park, S Park, J Lee, B Lee, H Lee Workshop on Document Intelligence at NeurIPS 2019, 2019 | 2 | 2019 |
| Adversarial dropout for recurrent neural networks S Park, K Song, M Ji, W Lee, IC Moon Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4699-4706, 2019 | 2 | 2019 |
| Disease-medicine topic model for prescription record mining S Park, D Choi, W Lee, D Jung, M Kim, IC Moon 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 86-93, 2014 | 1 | 2014 |
| Character Region Attention For Text Spotting Y Baek, S Shin, J Baek, S Park, J Lee, D Nam, H Lee European Conference on Computer Vision, 504-521, 2020 | | 2020 |
| CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks Y Baek, D Nam, S Park, J Lee, S Shin, J Baek, CY Lee, H Lee Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | | 2020 |
| Hierarchical prescription pattern analysis with symptom labels SJ Shin, JY Oh, S Park, M Kim, IC Moon 2015 IEEE International Conference on Data Mining Workshop (ICDMW), 178-187, 2015 | | 2015 |
