文颖 职称： 教授（研究员）
直属机构： 通信与电子工程学院
学科：





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个人资料
部门： 通信与电子工程学院
性别： 女
专业技术职务：
毕业院校： 上海交通大学
学位： 博士
学历： 研究生
联系电话：
电子邮箱： ywen@cs.ecnu.edu.cn
办公地址： 信息楼337
通讯地址： 上海市中山北路3663号
邮编：
传真：

教育经历
上海交通大学，电子信息与电气工程学院，博士研究生
上海大学，自动化学院，硕士研究生
合肥工业大学，电气工程学院自动化系，本科


工作经历
华东师范大学，通信与电子工程学院，教授
华东师范大学，计算机科学与技术系，副教授
美国哥伦比亚大学，脑图像实验室，博士后
邮政科学上海研究院，研究开发部，高级工程师






个人简介
致力于图像处理与人工智能领域研究，专注于医学图像处理、计算机视觉、机器学习、生物特征识别。先后主持国家自然科学基金面上项目、科技部、上海市科委、上海市教委等省部级以及企事业横向项目十余项。发表学术论文50余篇，包括TIP、TFS、TITS、Pattern Recognition、Magnetic resonance imaging、Expert Systems with Applications、Digital Signal Processing以及IEEE国际学术会议如AAAI、ICIP、ICASSP、IJCNN等多篇。申请发明专利9项，获授权4项。为多个国内外SCI期刊、国际会议和核心期刊审稿（包括TIS、PR、DSP、IJPRAI、ICPR、自动化学报、计算机学报等）。入选2012上海市浦江人才计划，获2015年度上海市科技进步一等奖、2019年度上海市科技进步二等奖、2019年度教育部科技进步二等奖。


社会兼职
IEEE member
CCF 会员
中国图象图形学学会会员



研究方向
计算机视觉、图像处理、机器学习与智能系统




开授课程
数字图像处理，机器学习



科研项目
1.科技创新2030-“新一代人工智能”重大项目
2. 国家自然科学基金面上项目
3.上海市自然科学基金面上项目
4. 上海市教委科技项目
5.教育部留学回国人员启动基金
6. 上海市浦江人才计划
7.国家科技支撑计划子课题
8. 企事业横项项目



学术成果
期刊论文：
1.Ying Wen, Cheng Xu, Yue Lu, Qingli Li et al., Gabor Feature-Based LogDemons With Inertial Constraint for Nonrigid Image Registration, IEEE Transactions on Image Processing, Vol. 29, 2020, 8238-8250.
2.Ying Wen,Le Zhanget al., Incorporation of Structural Tensor and Driving Force into Log-Demons for Large-deformation Image Registration, IEEE Transactions on Image Processing, Vol. 28, No. 12, December 2019, 6091-6102.
3.Shicheng Yang, Le Zhang, Ying Wen*, Sparse Low-Rank Component-Based Representation for Face Recognition with Low-Quality Images, IEEE Transaction on Information Forensics and Security, vol. 14, no. 1, January 2019, 251-261.
4.Ying Wen et al., Face Recognition Using Discriminative Locality Preserving Vectors, Digital signal processing, 50(2016) 103-113.
5.Ying Wen et al., Discriminant Sparsity Preserving Analysis for Face Recognition, International journal of pattern recognition and artificial intelligence, 30(2) 2016, **-1-12.
6.Xiaohua Wei, Shujing Lu, Ying Wen, Yue Lu. Recognition of Handwritten Chinese Address with Writing Variations, Pattern Recognition Letters, 73(2016):68-75.
7.Ying Wen et al., A Highly Accurate Symmetric Optical Flow based High-Dimensional Nonlinear Spatial Normalization of Brain Images, Magnetic Resonance Imaging 33 (2015) 465-473.
8.Ying Wen, A statistical approach to segmentation of diffusion tensor imaging, Bio-medical Materials and Engineering, 2014, 24:1253-1259.
9.L He, Ying Wen*, Meng Wan, Shuang Liu, Multi-channel features based automated segmentation of diffusion tensor imaging using an improved FCM with spatial constraints, Neurocomputing, 2014, 137: 107-114.
10.Ying Wen et al., Brain tissue classification based on DTI using an improved Fuzzy C-means algorithm with spatial constraints, Magnetic Resonance Imaging, 2013, 31(9):1623-1630.
11.Ying Wen et al., Face recognition using difference vector plus KPCA, Digital Signal Processing, 2012, 22(1): 140-146.
12.Ying Wen, A classifier for Bangla handwritten numeral recognition, Expert Systems with Applications, 2012, 39(1): 948-953.
13.Ying Wen, An improved discriminative common vectors and support vector machine based face recognition approach, Expert Systems with Applications, 2012, 39(4): 4628-4632.
14.Ying Wen, Yue Lu et al., An algorithm for license plate recognition applied to intelligent transportation system, IEEE transaction on intelligent transportation system, 2011, 12(3): 830-845.
15.Ying Wen, Pengfei Shi, An improved locally linear embedding for sparse data sets, International joural of pattern recognition and artificial intelligence, 2011, 25(5): 763-775.
16.Ying Wen, Yue Lu, Pengfei Shi, Handwritten Bangla numeral recognition system and its application to postal automation, Pattern Recognition, 2007, 40(1): 99-107.
17.Yue Lu, Xiaofu He, Ying Wen, Wang P.S.P, A new cow identification system based on iris analysis and recognition, International Journal of Biometrics, 2014, 6(1): 18-32.
18.Lihua Tang, Ying Wen* et al., Reduced field-of-view DTI segmentation of cervical spine tissue, Magnetic Resonance Imaging, 2013, 31(9): 1507-1514.
19.Zhenyu Zhou, Ying Wen et al., A conditional Granger causality model approach for group analysis in functional magnetic resonance imaging, Magnetic Resonance Imaging,2011,29(3):418-433.
20.Zhenyu Zhou, Ying Wen, Dongrong Xu, Automated artifact detection and removal for improved tensor estimation in motion-corrupted DTI data sets using the combination of local binary patterns and 2D partial least squares, Magnetic Resonance Imaging, 2011, 29(2): 230-242.
21.张子星，文颖*，基于分层置信度传播的光流估计方法，计算机系统应用，2018,27(9):25-32.
22.何冰，马泰，文颖* ，基于超像素和深度神经网络的高压输电线路环境检测，计算机系统应用，2020,29(1):250-255.

会议论文：
1.Ying Wen, Kai Xie, Segmenting Medical MRI via Recurrent Decoding Cell, AAAI 2020. (accepted)
2.Cheng Xu, Ying Wen*, Bing He, Fractional order derivate based Log-demons with driving force for high accurate image registration, IEEE International Conference on Acoustics, Speech and Signal Processing, 1997-2001, Brighton, United Kingdom, 2019.
3.Kai Xie,Ying Wen*,LSTM-MA: A LSTM method with multi-modality and adjacency constraint for brain image segmentation, IEEE International Conference on Image Processing, Sep.22-25, 2019, TaiPei, Taiwan, 240-244.
4.Jialiang Hu,Ying Wen*, Adaptive Fuzzy Clustering Algorithm with Local Information and Markov Random Field for Image Segmentation, ICONIP 2018, LNCS 11304, pp. 170–180, 2018.
5.Zixing Zhang, Ying Wen*, Inertial Constrained Hierarchical Belief Propagation for Optical Flow, PRICAI 2018, LNAI 11012, pp. 574–587, 2018.
6.Shicheng Yang, Ying Wen*, Sparse low-rank component coding for face recognition with illumination and corruption, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2018), 1693-1697.
7.Bing He, Ying Wen, Full convolution neural network combined with K-means clustering algorithm for image segmentation, Tenth international Conference of Digital Image Processing, 2018, Shanghai, China, vol.108062o-1.
8.Ying Wen, A Novel Dictionary Based SRC for Face Recognition, IEEE International Conference on Acoustics, Speech and Signal Processing, 2582-2586, New Orleans, USA, 2017.
9.Yangshi Cheng, Ying Wen*, A novel SRC based method for face recognition with low quality images, ICIP2017, Beijing, China, 3805-3809.
10.Ying Wen et al., Face Recognition using Locality Sparsity Preserving Projections, International Joint Conference on Neural Networks, 2016, pp.3600-3607.
11.Le Zhang and Ying Wen*, Log-Demons with Driving Force for Large Deformation Image Registration, International Joint Conference on Neural Networks, 2016, pp.3052-3059.
12.Ying Wen, Lili Hou, Null Space based Discriminant Sparse Representation Large Margin for Face Recognition, 2015 International Joint Conference on Neural Networks (IJCNN2015), 1-8.
13.Lili Hou, Le Zhang, Qiuying Yang, Ying Wen*, An Extended Fuzzy Local Information C-Means Clustering Algorithm, 2015 International Joint Conference on Neural Networks (IJCNN2015), 1-8.
14.Qiuying Yang, Ying Wen*, Zernike Moments Descriptor Matching based Symmetric Optical Flow for Motion Estimation and Image Registration, 2014 International Joint Conference on Neural Networks (IJCNN2014), 350-357, 2014.7.6-2014.7.11.
15.Ying Wen, Peterson, B.S., Dongrong Xu, A Highly Accurate, Optical Flow Based Algorithm for Nonlinear Spatial Normalization of Diffusion Tensor Images,2013 International Joint Conference on Neural Networks (IJCNN2013), 1-8, 2013.8.4-2013.8.9.
16.Ying Wen, Yue Lu, Discriminative common vectors based on the Gram-Schmidt reorthogonalization for the small sample size problem,IEEE International Conference on Acoustics, Speech and Signal Processing, 1325-1328, Kyoto, 2012.03.25-2012.03.30.
17.Ying Wen, Yue Lu, Discriminative common vectors based on the Gram-Schmidt reorthogonalization for the small sample size problem, IEEE International Conference on Acoustics, Speech and Signal Processing, 1325-1328, Kyoto, 2012.03.25-2012.03.30.
18.Ying Wen et al., An improved locally linear embedding for sparse data sets, Proceedings of 2010 IEEE 17th International Conference on Image Processing, 2010.09.26-2010.09.29.
19.Ying Wen, Pengfei Shi, A Novel Classifier for Handwritten Numeral Recognition, 2008 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2008.03.30-2008.04.04.
20.Ying Wen, Pengfei Shi, An Approach to Numeral Recognition based on Improved LDA and Bhattacharyya Distance, The third international symposium on Communications, Control and Signal Processing, 2008.03.12-2008.03.14.
21.Ying Wen, Pengfei Shi, Image PCA: A new approach for face recognition, 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2007.04.15-2007.04.20.

专利：
1.文颖，阳求应，一种非刚性脑图像配准方法, ZL3.2
2.文颖，侯丽丽，张乐，一种鲁棒性的FCM图像分割方法, CNB
3.文颖，张洪达,侯丽丽，一种基于共同向量词典的稀疏表示分类器, CNB
4.文颖，叶慎林，一种多路多通道高速数据流的实时分包解析方法, CNB
5.文颖，蒋婷，吕岳，一种塑封邮件图像地址块定位方法, CN2.8
6.文颖，谢恺，一种基于超像素和长短时记忆网络的图像分割方法，1.7
7.文颖，单昕昕，一种基于卷积神经网络和稀疏表示的部分人脸识别方法，4.0
8.文颖，沈庾涛，一种提高卷积神经网络分类性能的算法，1.6

软件著作权
1.基于复杂环境的车牌识别系统V1.0，No. 2014SR091540
2.多路多通道数据流实时解析系统[简称：数据流解析系统]V1.0，No. 2017SR672388
3.基于模糊聚类和马尔可夫模型的图像分割软件V1.0，No. 2019SR**




荣誉及奖励

2019年 上海市科技进步二等奖（1/8）
2019年 教育部科技进步二等奖（3/11）
2015年 上海市科技进步一等奖（2/15）
2012年 上海市浦江人才计划