| Soft-label anonymous gastric x-ray image distillation G Li, R Togo, T Ogawa, M Haseyama ICIP, 305-309, 2020 | 33 | 2020 |
| Compressed gastric image generation based on soft-label dataset distillation for medical data sharing G Li, R Togo, T Ogawa, M Haseyama Computer Methods and Programs in Biomedicine 227, 107189, 2022 | 27 | 2022 |
| Self-knowledge distillation based self-supervised learning for covid-19 detection from chest x-ray images G Li, R Togo, T Ogawa, M Haseyama ICASSP, 1371-1375, 2022 | 21 | 2022 |
| Tribyol: Triplet byol for self-supervised representation learning G Li, R Togo, T Ogawa, M Haseyama ICASSP, 3458-3462, 2022 | 18 | 2022 |
| Dataset distillation for medical dataset sharing G Li, R Togo, T Ogawa, M Haseyama AAAI Workshop, 1-6, 2023 | 16 | 2023 |
| Self-supervised learning for gastritis detection with gastric x-ray images G Li, R Togo, T Ogawa, M Haseyama International Journal of Computer Assisted Radiology and Surgery 18 (10 …, 2023 | 14 | 2023 |
| COVID-19 detection based on self-supervised transfer learning using chest X-ray images G Li, R Togo, T Ogawa, M Haseyama International Journal of Computer Assisted Radiology and Surgery 18 (4), 715-722, 2023 | 12 | 2023 |
| Dataset distillation using parameter pruning G Li, R Togo, T Ogawa, M Haseyama IEICE Transactions on Fundamentals of Electronics, Communications and …, 2023 | 12 | 2023 |
| Cross-view self-supervised learning via momentum statistics in batch normalization G Li, R Togo, T Ogawa, M Haseyama ICCE-TW, 1-2, 2021 | 7 | 2021 |
| Boosting automatic COVID-19 detection performance with self-supervised learning and batch knowledge ensembling G Li, R Togo, T Ogawa, M Haseyama Computers in Biology and Medicine 158, 106877, 2023 | 6 | 2023 |
| Triplet self-supervised learning for gastritis detection with scarce annotations G Li, R Togo, T Ogawa, M Haseyama GCCE, 787-788, 2021 | 5 | 2021 |
| Complexity evaluation of medical image data for classification problem based on spectral clustering G Li, R Togo, T Ogawa, M Haseyama GCCE (Best Student Paper), 667-669, 2020 | 4 | 2020 |
| Rgmim: Region-guided masked image modeling for covid-19 detection G Li, R Togo, T Ogawa, M Haseyama | 3 | 2023 |
| Awesome Dataset Distillation G Li, B Zhao, T Wang https://github.com/Guang000/Awesome-Dataset-Distillation, 2022 | 2 | 2022 |
| Dataset complexity assessment based on cumulative maximum scaled area under Laplacian spectrum G Li, R Togo, T Ogawa, M Haseyama Multimedia Tools and Applications 81 (22), 32287-32303, 2022 | 2 | 2022 |
| Importance-aware adaptive dataset distillation G Li, R Togo, T Ogawa, M Haseyama Neural Networks 172, 106154, 2024 | | 2024 |
| Zero-shot traffic sign recognition based on midlevel feature matching Y Gan, G Li, R Togo, K Maeda, T Ogawa, M Haseyama Sensors 23 (23), 9607, 2023 | | 2023 |
| A study on data-efficient learning and its medical applications G Li Hokkaido University, 2023 | | 2023 |
| A Note on Traffic Sign Recognition Based on Vision Transformer Adapter Using Visual Feature Matching Y Gan, G Li, R Togo, K Maeda, T Ogawa, M Haseyama ITE Technical Report 47 (6), 1-4, 2023 | | 2023 |
| Self-supervised transfer learning for COVID-19 detection from chest X-ray images G Li, R Togo, T Ogawa, M Haseyama AAAI Workshop, 1-6, 2022 | | 2022 |
Miki HaseyamaHokkaido UniversityVerified email at ist.hokudai.ac.jp
