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Yang yuqiao
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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
142021
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
102019
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
62022
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
12023
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
12022
SaSaMIM: Synthetic Anatomical Semantics-Aware Masked Image Modeling for Colon Tumor Segmentation in Non-contrast Abdominal Computed Tomography
P Dai, Y Ou, Y Yang, D Liu, M Hashimoto, M Jinzaki, M Miyake, K Suzuki
International Conference on Medical Image Computing and Computer-Assisted …, 2024
2024
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
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
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