| Improving unsupervised image clustering with robust learning S Park, S Han, S Kim, D Kim, S Park, S Hong, M Cha Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 30 | 2021 |
| Mitigating embedding and class assignment mismatch in unsupervised image classification S Han, S Park, S Park, S Kim, M Cha European Conference on Computer Vision, 768-784, 2020 | 19 | 2020 |
| Learning to score economic development from satellite imagery S Han, D Ahn, S Park, J Yang, S Lee, J Kim, H Yang, S Park, M Cha Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 15 | 2020 |
| Lightweight and robust representation of economic scales from satellite imagery S Han, D Ahn, H Cha, J Yang, S Park, M Cha Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 428-436, 2020 | 13 | 2020 |
| Elsa: Energy-based learning for semi-supervised anomaly detection S Han, H Song, S Lee, S Park, M Cha arXiv preprint arXiv:2103.15296, 2021 | 5 | 2021 |
| Take a chance: Managing the exploitation-exploration dilemma in customs fraud detection via online active learning S Kim, TD Mai, TND Khanh, S Han, S Park, K Singh, M Cha arXiv preprint arXiv:2010.14282, 2020 | 4 | 2020 |
| Learning economic indicators by aggregating multi-level geospatial information S Park, S Han, D Ahn, J Kim, J Yang, S Lee, S Hong, J Kim, S Park, ... Proceedings of the Association for the Advanced of Artificial Intelligence …, 2022 | 3 | 2022 |
| Classification of Goods Using Text Descriptions With Sentences Retrieval E Lee, S Kim, S Kim, S Park, M Cha, S Jung, S Yang, Y Choi, S Ji, M Song, ... arXiv preprint arXiv:2111.01663, 2021 | 2 | 2021 |
| Knowledge Sharing via Domain Adaptation in Customs Fraud Detection S Park, S Kim, M Cha arXiv preprint arXiv:2201.06759, 2022 | 1 | 2022 |
| Active Learning for Human-in-the-Loop Customs Inspection S Kim, TD Mai, S Han, S Park, T Nguyen, J So, K Singh, M Cha IEEE Transactions on Knowledge and Data Engineering, 2022 | 1 | 2022 |
| A Comprehensive and Adversarial Approach to Self-Supervised Representation Learning YZ Xu, S Han, S Park, M Cha, CT Li 2020 IEEE International Conference on Big Data (Big Data), 709-717, 2020 | 1 | 2020 |
| A Comprehensive Approach to Unsupervised Embedding Learning based on AND Algorithm S Han, Y Xu, S Park, M Cha, CT Li arXiv preprint arXiv:2002.12158, 2020 | 1 | 2020 |
| Downscaling Earth System Models with Deep Learning S Park, K Singh, A Nellikkattil, E Zeller, TD Mai, M Cha Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | | 2022 |
| FedX: Unsupervised Federated Learning with Cross Knowledge Distillation S Han, S Park, F Wu, S Kim, C Wu, X Xie, M Cha arXiv preprint arXiv:2207.09158, 2022 | | 2022 |
| IMAGE ANALYSIS SYSTEM AND OPERATING METHOD OF THE SAME M Cha, S Han, S Park, S Kim, S Park US Patent App. 17/375,650, 2022 | | 2022 |
| Weakly supervised method to predict economic development: A case study for Nepal and Cambodia D Ahn, J Yang, S Park, S Han, E Lee, S Lee, H Yang, S Park, J Kim, ... Data-driven Humanitarian Mapping Workshop 2021, 2021 | | 2021 |
| A Comprehensive and Adversarial Approach to Unsupervised Embedding Learning Y Xu, S Han, S Park, M Cha, CT Li 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020 | | 2020 |
| Teaching Machines to Measure Economic Activities from Satellite Images: Challenges and Solutions D Ahn, M Cha, S Han, J Kim, S Lee, S Park, S Park, H Yang, J Yang | | 2020 |
| FedX: Unsupervised Federated Learning with Cross Knowledge Distillation | | |
| Human-in-the-loop solution for scoring economic development from geospatial data S Park, D Ahn, S Han, E Lee, D Kim, J Yang, S Lee, S Park, H Yang, J Kim, ... | | |
Meeyoung ChaKAIST & IBSVerified email at kaist.ac.kr
