个人简历

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
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。

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

专利：
1. 文颖，阳求应，一种非刚性脑图像配准方法, ZL201310703933.2
2. 文颖，侯丽丽，张乐，一种鲁棒性的FCM图像分割方法, CN105654453B
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, CN105574475B
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, CN107172037B
5. 文颖，蒋婷，吕岳，一种塑封邮件图像地址块定位方法, CN201610801172.8
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，201811560271.7
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，202010267944.0
8. 文颖，沈庾涛，一种提高卷积神经网络分类性能的算法，201911291641.6
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. 2019SR0101614
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

研究领域

计算机视觉，模式识别与智能系统　""

近期论文

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 Zhang et 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, 1656003-1-12.
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.
IEEE member
CCF 会员
中国图象图形学学会会员