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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
122021
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
72019
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
22022
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
AI-aided Diagnosis of Rare Soft-Tissue Sarcoma by Means of Massive-Training Artificial Neural Network (MTANN)
Yang Y., Jin Z., Nakatani F., Miyake M., Suzuki K.
5th Annual International Conference of the IEEE Engineering in Medicine and …, 2023
2023
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
2022
Federated Learning Coupled with Massive-Training Artificial Neural Networks in Tumor Segmentation in CT Images.
Y Yang, Z Jin, K Suzuki
The 44th International Conference of the IEEE Engineering in Medicine and …, 2022
2022
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
Segmentation of Liver Tumor in Hepatic CT by Using MTANN Deep Learning with Small Training Dataset Size.
SK Sato M, Yang Y, Jin Z
The 6th International Symposium on Biomedical Engineering (ISBE2021), 2021
2021
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