史恩泽

——2024级博士研究生——

· 研究方向

EEG脑电信号处理,脑机接口

· 邮箱

ezshi@mail.nwpu.edu.cn

· 代表论文

方法题目链接
Shu Zhang*, Enze Shi*, Lin Wu, Ruoyang Wang, Sigang Yu, Zhengliang Liu, Shaochen Xu, Tianming Liu, Shijie Zhao. Differentiating Brain States via Multi-clip Random Fragment Strategy-Based Interactive Bidirectional Recurrent Neural Network. Neural Networks, 2023. (Accepted)[PaperLink] [Code]
Enze Shi, Sigang Yu, Yanqing Kang, Jinru Wu, Lin Zhao, Weizhong Liu, Dajiang Zhu, Jinglei Lv, Tianming Liu, Xintao Hu, Shu Zhang. MEET: Multi-band EEG Transformer. IEEE Transactions on Biomedical Engineering (T-BME), 2023. (under review)[PaperLink] [Code]
Shu Zhang*, Lin Wu*, Sigang Yu, Enze Shi, Ning Qiang, Huan Gao, Jingyi Zhao, Shijie Zhao. An Explainable and Generalizable Recurrent Neural Network Approach for Differentiating Human Brain States on EEG Dataset[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022: 1-12.[PaperLink] [Code]
Sigang Yu, Enze Shi, Ruoyang Wang, Shijie Zhao, Tianming Liu, Xi Jiang, Shu Zhang. A hybrid learning framework for fine-grained interpretation of brain spatiotemporal patterns during naturalistic functional magnetic resonance imaging. Frontiers in Human Neuroscience, 2022, 16.[PaperLink] [Code]
Shu Zhang*, Jinru Wu*, Enze Shi, Sigang Yu, Yongfeng Gao, Lihong Connie Li, Licheng Ryan Kuo, Zhengrong Liang. MM-GLCM-CNN: A Multi-scale and Multi-level based GLCM-CNN for Polyp Classification. Computerized Medical Imaging and Graphics, 2023.[PaperLink] [Code]
Shu Zhang*, Jinru Wu*, Sigang Yu, Ruoyang Wang, Enze Shi, Yongfeng Gao, Zhengrong Liang. A Bagging Strategy-Based Multi-scale Texture GLCM-CNN Model for Differentiating Malignant from Benign Lesions Using Small Pathologically Proven Dataset. Multiscale Multimodal Medical Imaging: Third International Workshop, MMMI 2022.[PaperLink] [Code]
Shu Zhang*, Yanqing Kang*, Sigang Yu, Jinru Wu, Enze Shi, Ruoyang Wang, Zhibin He, Lei Du, Tuo Zhang. A Novel Two-Stage Multi-view Low-Rank Sparse Subspace Clustering Approach to Explore the Relationship Between Brain Function and Structure. Machine Learning in Medical Imaging: 13th International Workshop, MLMI 2022.[PaperLink] [Code]

· 出版论文

[1] Shu Zhang*, Enze Shi*, Lin Wu, Ruoyang Wang, Sigang Yu, Zhengliang Liu, Shaochen Xu, Tianming Liu, Shijie Zhao. Differentiating Brain States via Multi-clip Random Fragment Strategy-Based Interactive Bidirectional Recurrent Neural Network. Neural Networks, 2023. (under review)

[2] Enze Shi, Sigang Yu, Yanqing Kang, Jinru Wu, Lin Zhao, Weizhong Liu, Dajiang Zhu, Jinglei Lv, Tianming Liu, Xintao Hu, Shu Zhang. MEET: Multi-band EEG Transformer. IEEE Transactions on Biomedical Engineering (T-BME), 2023. (under review)

[3] Shu Zhang, Lin Wu, Sigang Yu, Enze Shi, Ning Qiang, Huan Gao, Jingyi Zhao, Shijie Zhao. An Explainable and Generalizable Recurrent Neural Network Approach for Differentiating Human Brain States on EEG Dataset[J]. IEEE Transactions on Neural Networks and Learning Systems, 2022: 1-12.

[4] Sigang Yu, Enze Shi, Ruoyang Wang, Shijie Zhao, Tianming Liu, Xi Jiang, Shu Zhang. A hybrid learning framework for fine-grained interpretation of brain spatiotemporal patterns during naturalistic functional magnetic resonance imaging[J]. Frontiers in Human Neuroscience, 2022, 16.

[5] Shu Zhang, Jinru Wu, Sigang Yu, Ruoyang Wang, Enze Shi, Yongfeng Gao, Zhengrong Liang. A Bagging Strategy-Based Multi-scale Texture GLCM-CNN Model for Differentiating Malignant from Benign Lesions Using Small Pathologically Proven Dataset[C]//Multiscale Multimodal Medical Imaging: Third International Workshop, MMMI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Cham: Springer Nature Switzerland, 2022.

[6] Shu Zhang, Jinru Wu, Enze Shi, Sigang Yu, Yongfeng Gao, Lihong Connie Li, Licheng Ryan Kuo, Zhengrong Liang. MM-GLCM-CNN: A Multi-scale and Multi-level based GLCM-CNN for Polyp Classification. Computerized Medical Imaging and Graphics, 2023. (under Review)

[7] Shu Zhang, Yanqing Kang, Sigang Yu, Jinru Wu, Enze Shi, Ruoyang Wang, Zhibin He, Lei Du, Tuo Zhang. A Novel Two-Stage Multi-view Low-Rank Sparse Subspace Clustering Approach to Explore the Relationship Between Brain Function and Structure. Machine Learning in Medical Imaging: 13th International Workshop, MLMI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings. Cham: Springer Nature Switzerland, 2022: 191-200.