| 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 | 395 | 2019 |
| 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 | 155 | 2018 |
| Swad: Domain generalization by seeking flat minima J Cha, S Chun, K Lee, HC Cho, S Park, Y Lee, S Park Advances in Neural Information Processing Systems 34, 22405-22418, 2021 | 123* | 2021 |
| 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 | 76 | 2020 |
| Efficient extraction of domain specific sentiment lexicon with active learning S Park, W Lee, IC Moon Pattern Recognition Letters 56, 38-44, 2015 | 73 | 2015 |
| Dirichlet variational autoencoder W Joo, W Lee, S Park, IC Moon Pattern Recognition 107, 107514, 2020 | 63 | 2020 |
| Show, attend and distill: Knowledge distillation via attention-based feature matching M Ji, B Heo, S Park Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 7945-7952, 2021 | 59 | 2021 |
| BROS: A Layout-Aware Pre-trained Language Model for Understanding Documents T Hong, D Kim, M Ji, W Hwang, D Nam, S Park CoRR, Vol. abs/2108.04539 (2021). showeprint [arXiv] 2108, 2021 | 57* | 2021 |
| Character region attention for text spotting Y Baek, S Shin, J Baek, S Park, J Lee, D Nam, H Lee Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 42 | 2020 |
| 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 | 35 | 2018 |
| 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 | 28 | 2017 |
| 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 | 26 | 2019 |
| 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 | 23 | 2019 |
| Domain generalization by mutual-information regularization with pre-trained models J Cha, K Lee, S Park, S Chun Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 22 | 2022 |
| SynthTIGER: synthetic text image GEneratoR towards better text recognition models M Yim, Y Kim, HC Cho, S Park Document Analysis and Recognition–ICDAR 2021: 16th International Conference …, 2021 | 13 | 2021 |
| 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 | 12 | 2020 |
| Multi-modal text recognition networks: Interactive enhancements between visual and semantic features B Na, Y Kim, S Park Computer Vision–ECCV 2022: 17th European Conference, Tel Aviv, Israel …, 2022 | 9 | 2022 |
| Contrastive learning for knowledge tracing W Lee, J Chun, Y Lee, K Park, S Park Proceedings of the ACM Web Conference 2022, 2330-2338, 2022 | 8 | 2022 |
| 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 | 8 | 2015 |
| Associative topic models with numerical time series S Park, W Lee, IC Moon Information Processing & Management 51 (5), 737-755, 2015 | 7 | 2015 |
Il-Chul MoonAssociate Professor, Department of Industrial and Systems Engineering, KAISTVerified email at kaist.ac.kr
