尹明
姓 名：尹 明
最高学历：博士研究生
目前职位：教 授
科研方向：智能信息处理，电路与系统
E-mail: m.yin@scnu.edu.cn
Homepage: https://www.researchgate.net/profile/Ming_Yin3
中国计算机学会高级会员，中国图象图形学学会高级会员，中国自动化学会模式识别与机器智能专委会委员，人工智能学会模式识别专委会委员，图象图形学学会 CSIG机器视觉专委会委员。于2006年获华中科技大学信息与通信工程专业博士学位。主持和参与国家自然科学基金、广东省自然科学基金等10多项纵、横向科研项目。已发表80余篇主要学术论文，其中20余篇发表在IEEE TPAMI、IEEE TIP、IEEE TNNLS、IEEE JSTSP、CVIU等国际Top期刊和CVPR、AAAI、ICIP、ICASSP、 IJCNN等计算机学会推荐国际学术会议，其中入选ESI高被引论文2篇。入选2023年度“全球前2%顶尖科学家榜单”（World's Top 2% Scientists）。发明专利授权3项，申请6项；软件著作权授权2项。获得过计算机学会(CCF)科学技术奖自然科学一等奖、教育部科学技术进步奖一等奖等奖项。指导学生多次参加全国大学生电子设计竞赛并获奖。
“吾生也有涯，而知也无涯”，欢迎报考我的研究生（电路与系统，电子信息），并师生共勉！
科研项目：
1. 广东省自然科学基金面上项目:“面向多视图数据的共享生成式隐特征表示学习”，2020.1- 2021.12，负责人
2. 国家自然科学基金面上项目: “基于子空间学习的多视图鲁棒一致性表达研究”，2019.1- 2022.12，负责人
3. 国家自然科学基金面上项目: “基于数据驱动的联合药效动力学及精准靶控理论与方法研究”，2018.1 - 2021.12，联合负责人
3. 国家自然科学基金-广东联合基金项目: “工业过程数据实时获取与知识自动化的理论与技术研究”，2018.1- 2021.12，排名第四
4. 广东省教育厅科研项目: “面向工业大数据的低秩子空间聚类方法”，2018.4- 2020.4，负责人
5. 广东省科技计划项目: “基于人体运动大数据分析的运动康复系统”，2017.1- 2019.12，负责人
6. 广东省自然科学基金自由申请项目(2014A030313511):“高阶张量表示的视频压缩感知方法研究”，2015.1- 2018.1，负责人
7. 教育部留学回国人员科研启动基金:“图正则化的低秩表示方法及其在高维数据聚类分析中的应用”，2015.6- 2018.6，负责人
近期发表论文：
期刊论文Journal:
1. Shuwan Ma,Yonghua Wang,Jinxuan Ren, Ming Yin. A Cooperative Spectrum Sensing Method Based on Soft Low-Rank Subspace Clustering. IEEE Transactions on Circuits and Systems--II: Express Briefs, 2022, 69(9):3954-3958.
2. ijuan Wang, Lin Zhang, Ming Yin*, Zhifeng Hao, Ruichu Cai, Wen Wen. Double embedding-transfer-based multi-view spectral clustering, Expert Systems With Applications, 2022. Doi: 10.1016/j.eswa.2022.118374. (通讯作者)
3. Guoliang He, Wenjun Jiang, Rong Peng, Ming Yin*, Min Han. Soft Subspace Based Ensemble Clustering for Multivariate Time Series Data. IEEE Transactions on Neural Networks and Learning Systems. 2022. Doi: 10.1109/TNNLS.2022.3146136. (通讯作者)
4. Zixi Liang, Ming Yin*, Junli Gao, Yicheng He, Weitian Huang.View knowledge transfer network for multi-view action recognition, Image and Vision Computing, 2022, vol.118, 104357. (通讯作者)
5. 尹明,吴浩杨,谢胜利,杨其宇. 基于自注意力对抗的深度子空间聚类, 自动化学报. 2022, 48(1): 271−281.
6. Toufique A. Soomro1, Lihong Zheng, Ahmed J. Afifi, Ahmed Ali, Ming Yin* and Junbin Gao. Artificial intelligence (AI) for medical imaging to combat coronavirus disease (COVID-19): a detailed review with direction for future research. Artificial Intelligence Review, 2022, vol.55, pages:1409–1439. (通讯作者)
7. Feiran Jie, Qingfeng Nie, Mingsuo Li, Ming Yin, Taisong Jin.Atrous spatial pyramid convolution for object detection with encoder-decoder, Neurocomputing, 2021, vol.464, Pages 107-118.
8. Zongze Wu, Chunchen Su, Ming Yin, Zhigang Ren,Shengli Xie. Subspace clustering via stacked independent subspace analysis networks with sparse prior information. Pattern Recognition Letters, 2021, 146:165-171.
9. Ming Yin, WeiLiu, MingsuoLi, TaisongJin and RongrongJi. Cauchy loss induced block diagonal representation for robust multi-view subspace clustering. Neurocomputing, 2021, 427(2): 84-95.
10. Lijuan Wang, Jiawen Huang, Ming Yin*, Ruichu Cai, Zhifeng Hao. Block diagonal representation learning for robust subspace clustering. Information Sciences, 2020, 526 (7): 54–67. (通讯作者)
11. Toufique A. Soomro, Ming Yin*, and Junbin Gao. Impact of Image Enhancement Technique on CNN Model for Retinal Blood Vessels Segmentation. IEEE Access. 2019,7(10):158183-158197. (通讯作者)
12. Weitian Huang, Ming Yin*, Jianzhong Li, and Shengli Xie, Deep Clustering via Weighted k-Subspace Network, IEEE Signal Processing Letters, 2019, 26(11): 1628-1632. Doi: 10.1109/LSP.2019.2941368 ( 通讯作者)
13. Ming Yin, Junbin Gao, Shengli Xie and Yi Guo. Multiview Subspace Clustering via Tensorial t-Product Representation. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(3): 851-864.
14. Shengxiang Gao, Zhengtao Yu, Taisong Jin, Ming Yin. Multi-view low-rank matrix factorization using multiple manifold regularization, Neurocomputing, 2019, 335:143–152.
15. Ming Yin, Deyu Zeng, Junbin Gao, Zongze Wu and Shengli Xie. Robust Multinomial Logistic Regression Based on RPCA, IEEE Journal of Selected Topics in Signal Processing, 2018, 12(6): 1144-1154. Doi:10.1109/JSTSP.2018.2872460. ( SCI, JCR2, IF: 4.361)
16. Ming Yin, Shengli Xie, Zongze Wu, Yun Zhang, Junbin Gao. Subspace Clustering via Learning an Adaptive Low-rank Graph. IEEE Transactions on Image Processing (TIP), 2018, 27(8): 3716-3728. ( SCI, JCR2, IF: 4.828)
17. Ming Yin, Zongze Wu, Daming Shi, Junbin Gao, Shengli Xie. Locally Adaptive Sparse Representation on Riemannian Manifolds for Robust Classification, Neurocomputing, 2018, Volume 310, Pages 69-76.
18. Ming Yin, ZongZe Wu, Deyu Zeng, Panshuo Li and Shengli Xie. Sparse Subspace Clustering with Jointly Learning Representation and Affinity Matrix. Journal of the Franklin Institute, Volume 355, Issue 8, 2018, Pages 3795-3811.
19. Wu, Z., Ming Yin, Zhou, Y. et al. Robust Spectral Subspace Clustering Based on Least Square Regression. Neural Processing Letters, 2018,48(3):1359–1372. (通讯作者)
20. Ming Yin, Junbin Gao, Zhouchen Lin. Laplacian Regularized Low-Rank Representation and Its Applications, IEEE Transactions on Pattern Analysis and Machine Intelligence, (TPAMI), 2016, 38(3):504-517.
21. Ming Yin, Junbin Gao, Zhouchen Lin, Qinfeng Shi and Yi Guo. Dual Graph Regularized Latent Low-rank Representation for Subspace Clustering. IEEE Transactions on Image Processing (TIP), 2015, 24(12):4918-4933.
22. Ming Yin, Junbin Gao, Yi Guo. A Nonlinear Low-rank Representation on Stiefel Manifold. Electronics Letters, 2015, 51(10):749-751.
23. Ming Yin, Junbin Gao, Shuting Cai. Image Super-resolution via 2D Tensor Regression Learning. Computer Vision and Image Understanding, 2015, 132: 12-23.
24. Guo Fen, Min Huaqing and Yin Ming. A self-aware strategy for Virtual machines placement on clouds. Computer Modelling and New Technologies. 2014, 18(11):529-535.
25. Ming Yin, Junbin Gao, Daming Shi, Shuting Cai. Band-level Correlation Noise Modeling for Wyner-Ziv Video Coding with Gaussian Mixture Models. Circuits, Systems & Signal Processing, 2015, 34(7):2237-2254.
26. Ming Yin, Junbin Gao, David Tien, Shuting Cai. Blind image deblurring via coupled sparse representation. Journal of Visual Communication and Image Representation, 2014, 25:814-821.
27. 尹明, 蔡述庭, 谢云. 基于高斯混合模型的Wyner-Ziv视频编码. 计算机学报, 35(1):173-182, 2012.
28. 尹明,蔡述庭,谢云. 基于量化噪声因素的分布式视频编码的虚拟相关信道模型. 通信学报, 33(2):141-148，2012.
会议论文Conference:
1. Ming Yin*, Weitian Huang, Junbin Gao. Shared Generative Latent Representation Learning for Multi-view Clustering. AAAI Conference on Artificial Intelligence (AAAI-20), 2020, 6688-6695. (CCF A类会议)
2. Kai Zou, Ming Yin*, Weitian Huang, and Yiqiu Zeng. Deep Stacked Bidirectional LSTM Neural Network for Skeleton-Based Action Recognition. The 10th International Conference on Image and Graphics (ICIG 2019), pp. 1–13, 2019.
3. Deyu Zeng, Ming Yin*, et al. Robust regression with nonconvex schatten p-norm minimization. International Conference on Neural Information Processing (ICONIP) , 2018, pages 498-508. (通信作者)
4. Chunchen Su, Zongze Wu, Ming Yin*, Kaixin Li, and Weijun Sun. Subspace clustering via independent subspace analysis network. IEEE International Conference on Image Processing (ICIP), 2017, pages 4217- 4221. (通信作者)
5. Ming Yin, Yi Guo, Junbin Gao, Shengli Xie and Zhaoshui He. Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds. In The IEEE Conference on Computer Vision and Pattern Recognition(CVPR) 2016, pages 5157-5164, (CCF A类会议)
6. Ming Yin, Xiaozhao Fang and Shengli Xie. Semi-supervised Sparse Subspace Clustering on Symmetric Positive Definite Manifolds. CCPR2016,Vol.662, pp 601-611. (全国模式识别学术会议)
7. Yi Guo, Junbin Gao, Stephen Tierney, Feng Li and Ming Yin. Low Rank Sequential Subspace Clustering. The annual International Joint Conference on Neural Networks(IJCNN) 2015, p:1-8, doi:10.1109/IJCNN.2015.7280328. (CCF C类会议)
8. Ming Yin, Junbin Gao, Yangfen Sun and Shuting Cai. Blocky Artifact Removal with Low-Rank Matrix Recovery. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2014, p: 2015-2019. (CCF C类会议)
9. Ming Yin, Yi Guo and Junbin Gao. Linear Subspace Learning via Sparse Dimension Reduction. The annual International Joint Conference on Neural Networks(IJCNN) 2014, p:3540-3547. (oral presentation)(CCF C类会议)
10. Ming Yin, Shuting Cai and Junbin Gao. Robust Face Recognition via Double Low-Rank Matrix Recovery for feature extraction. IEEE International Conference on Image Processing (ICIP), 2013, p: 3770-3774. (CCF C类会议)
11. Junbin Gao, Yi Guo and Ming Yin. Restricted Boltzmann Machine Approach to Couple Dictionary Training for Image Super-Resolution, IEEE International Conference on Image Processing (ICIP), 2013, p: 499-503. (CCF C类会议)
教学活动：
1. 主讲本科生课程：《嵌入式系统及其应用》、《数字图像处理》
2. 指导学生参加全国大学生电子设计大赛、全国大学生“恩智浦”杯智能汽车竞赛、 "广东省高等学校大学生创新实验项目"等。
获奖情况：
1、林宙辰、刘光灿、尹明、俞勇. 高维复杂数据的低秩模型理论与方法. 2020年CCF科学技术奖自然科学一等奖
2、尹明 . 指导本科生参加2017年全国大学生“恩智浦”杯智能汽车竞赛,三等奖，教育部高等教育司
3、尹明 . 指导本科生参加2011年全国大学生电子设计竞赛，广东省二等奖
4、尹明 . 指导本科生参加2007年全国大学生电子设计竞赛，广东省二等奖