| Joint representation learning of legislator and legislation for roll call prediction Y Yang, X Lin, G Lin, Z Huang, C Jiang, Z Wei Proceedings of the Twenty-Ninth International Conference on International …, 2021 | 14 | 2021 |
| Extract, transform and filling: A pipeline model for question paraphrasing based on template Y Gu, Y Yuqiao, Z Wei Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019 …, 2019 | 9 | 2019 |
| FedAL: An Federated Active Learning Framework for Efficient Labeling in Skin Lesion Analysis Z Deng, Y Yang, K Suzuki, Z Jin 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2022 | 5 | 2022 |
| Federated Tumor Segmentation with Patch-Wise Deep Learning Model Y Yang, Z Jin, K Suzuki International Workshop on Machine Learning in Medical Imaging, 456-465, 2022 | 2 | 2022 |
| Decentralized Diagnostics: The Role of Federated Learning in Modern Medical Imaging W Rahmaniar, Z Deng, Y Yang, Z Jin, K Suzuki Advances in Intelligent Disease Diagnosis and Treatment: Research Papers in …, 2024 | | 2024 |
| Federated Active Learning Framework for Efficient Annotation Strategy in Skin-lesion Classification Z Deng, Y Yang, K Suzuki Journal of Investigative Dermatology, 2024 | | 2024 |
| Sparse Anatomical Prompt Semi-Supervised Learning with Masked Image Modeling for CBCT Tooth Segmentation P Dai, Y Ou, Y Yang, Y Liu, Y Zhao 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-5, 2024 | | 2024 |
| “Small-data” Patch-wise Multi-dimensional Output Deep-learning for Rare Cancer Diagnosis in MRI under Limited Sample-size Situation Y Yang, Z Jin, F Nakatani, M Miyake, K Suzuki 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1945-8452, 2024 | | 2024 |
| Development of a small-data deep-learning model based on an MTANN for soft tissue sarcoma diagnosis in MRI. Yang Y., Jin Z., Nakatani F., Miyake M., Suzuki K. Program of Scientific Assembly and Annual Meeting of Radiological Society of …, 2023 | | 2023 |
| Explaining Massive-Training Artificial Neural Networks in Medical Image Analysis Task Through Visualizing Functions Within the Models Z Jin, M Pang, Y Yang, FP Mahdi, T Qu, R Sasage, K Suzuki International Conference on Medical Image Computing and Computer-Assisted …, 2023 | | 2023 |
| Liver Tumor Segmentation by Using a Massive-Training Artificial Neural Network (MTANN) and its Analysis in Liver CT. Y Yang, M Sato, Z Jin, K Suzuki IEICE Technical Report; IEICE Tech. Rep., 2022 | | 2022 |
| Decentralized Diagnostics: The Role of Federated Learning in Modern W Rahmaniar, Z Deng, Y Yang, Z Jin, K Suzuki Advances in Intelligent Disease Diagnosis and Treatment: Research Papers in …, 0 | | |
Kenji SuzukiProfessor of Biomedical AI, Institute of Innovative Research, Tokyo Institute of Technology在 m.titech.ac.jp 的电子邮件经过验证
