葉茂：男，電子科技大學教授。博士，1973年9月出生。2008年破格提升為博士生指導教師，2009年破格晉升為正教授，中國工程物理研究院客座教授，電子科技大學機器人中心副主任。計算機學會計算機視覺專委會,多媒體計算專委會委員。2002年從香港中文大學獲得計算數學哲學博士學位並加入電子科技大學至今。曾於2005 - 2006年, 2010年分別在昆士蘭大學和賓夕法利亞大學做訪問學者。入選2006年教育部新世紀優秀人才支持計畫,第九屆四川省學術與技術帶頭人後備人選，四川省傑出青年學科帶頭人支持計畫。目前主要研究領域為機器學習與計算機視覺，已發表論文70餘篇，其中國際一流SCI期刊論文50餘篇，論文被引用700+次。主持或者作為骨幹成員參加如973、國家自然科學基金、四川省科技廳等各個國家、省部級課題。並主持開發多個取得良好經濟效益的工業產品項目；已授權發明專利8項；擔任多個國際學術會議程式委員會成員和分會場主席，如國際神經網路研討會（ISNN），通訊，電路與系統國際會議，高級數據挖掘與套用國際會議（ADMA）等。擔任中科院工程技術領域2區期刊Engineering Applications of Artificial Intelligence編委,多個國際一流期刊審稿人如IEEE Trans. NNLS, IEEE Trans. Cybernetics, IEEE Trans. Signal Processsing, IEEE Signal Processing Letters等。榮獲2012年華為-電子科技大學優秀合作團隊
學習經歷,工作經歷,研究項目,論文列表,教學工作,其他信息,
學習經歷
1991.09 -1995.07 學士四川師範大學基礎數學
1995.09 -1998.07碩士電子科技大學套用數學
2008.09- 2012.07博士香港中文大學計算數學
工作經歷
1998.07 -1999.07 助理工程師中電第29研究所
2002.07-2005.07講師電子科技大學
2005.07-2009.07副教授電子科技大學
2009.07-至今教授電子科技大學
研究項目
[1]基於特徵學習的領域自適應目標檢測方法研究項目2014.01-2017.12國家級國家級自然科學基金;
[2]盲信號分離若干基本問題的研究2008.01-2010.12國家級國家級自然科學基金;
[3]盲信號分離研究2007.01-2009.12省部級教育部新世紀優秀人才支持計畫
[4]基於視覺異常行為監控若干關鍵問題研究2009.5-2011.12省部級四川省青年基金
[5]社會服務機器人行為感知與控制神經計算方法研究2016.1-2018.12省部級四川省科技廳
[6]數字免疫網路研究2006.1-2007.12省部級四川省科技廳
論文列表
[1] Xudong Li, Mao Ye*, Dan Liu, Feng Zhang, Song Tang, Memory-based Object Detection in Surveillance Scenes, ICME2016. [2] Song Tang, Mao Ye*, Qihe Liu, and Fan Li, Domain adaptation of image classification based on collective target nearest neighbor representation, Journal of Electronic Imaging, Journal of Electronic Imaging 25(3), 033006, 2016 [3] Chenxue Yang, Mao Ye*, Song Tang, Zijian Liu, Tao Xiang, Semi-supervised low-rank representation for image classification, Signal, Image and Video Processing, 2016 Accept [4] Chenfei Xu, Qihe Liu, Mao Ye*, Age invariant face recognition and retrieval by coupled auto-encoder, Neuocomputing, 2016 accept [5] Lishen Pei, Mao Ye* , Xuezhuan Zhao, Yumin Dou and Jiao Bao, Action recognition by learning temporal slowness invariant features, The Visual Computer, 32:1395–1404,2016 [6] Yumin Dou, Pei Xu, Mao Ye* , Xue Li, Lishen Pei, Xudong Li, Real-time Multi-class Object Detection Using Two Dimensional Index, Journal of Real-Time Image Processing, 2015 Accept [7]Xiang Tao, Tao Li, Mao Ye* , and Xudong Li，Discriminative boosted forest with convolutional neural network-based patch descriptor for object detection, J. Electron. Imaging 25(1), 013002 (2016). [8]Tao Xiang, Tao Li, Mao Ye * and Zijian Liu, Random Forest with Adaptive Local Template for Pedestrian Detection, Mathematical Problems in Engineering, 767423, 2015 |
[10] Lishen Pei, Mao Ye*, Pei Xu, Tao Li, Fast Multi-Class Action Recognition by Querying Inverted Index Tables, Multimedia Tools and Applications, Volume 74, Issue 23 (2015), Page 10801-10822
[11]Xudong Li, Mao Ye*, Min Fu, Pei Xu and Tao Li, Domain Adaption of Vehicle Detector Based on Convolutional Neural Networks, International Journal of Control, Automation and Systems, Volume 13, Number 4, August 2015
[12]Renjie Huang, Mao Ye*, Pei Xu, Tao Li, Yumin Dou, Learning to Pool High-level Features for Face Representation, The Visual Computer, Vol 31, No 12, Page 1683-1695, 2015
[13]Pei Xu, Mao Ye*, etc, Dynamic Background Learning through Deep Auto-encoder Networks, ACM MM2014
[14]Pei Xu, Mao Ye*, etc, Motion detection via a couple of autoencoder networks. ICME2014
[15]Renjie Huang, Tao Li, Mao Ye* and Pei Xu, Unconstrained Face Verification by Optimally Organizing Multiple Classifiers, International Journal of Control, Automation and Systems, IJCAS Vol 12, No 4, August 2014
[16]Lishen Pei, Mao Ye*, Xuezhuan Zhao, Tao Xiang and Tao Li, Learning Spatio-Temporal Features for Action Recognition from the Side of the Video, Signal, Image and Video Processing, 10(1), 199-206, 2014
[17]Chenxue Yang, Tao Li, Mao Ye*, Zijian Liu and Bao Jiao, A Constrained Algorithm based NMF_\alpha for Image Representation, Discrete Dynamics in Nature and Society, Volume 2014, Article ID 179129,2014
[18]Chenxue Yang, Mao Ye*, Xudong Li, Zijian Liu, Tao Li, Robust Low Rank Image Representations by Deep Matrix Decompositions, Electronics Letters, 50(24):1843-1845, 2014
[19]Lishen Pei, Mao Ye*, Pei Xu, Xuezhuan Zhao, Guanjun Ge, One Example Based Action Detection In Hough Space. Multimedia Tools and Applications, 72(2): 1751-1772 (2014)
[20]Tao Li, Mao Ye* and Jian Ding, Discriminative Hough context model for object detection, The Visual Computer. Vol 30, Issue 1 (2014), Page 59-69
[21]Chenxue Yang, Mao Ye and Zijian Liu, An impulsive periodic single-species Logistic system with diffusion, Journal of Applied Mathematics. Vol.2013,101238,2013
[22]Pei Xu, Mao Ye*, Xue Li, Lishen Pei and Pengwei Jiao, Object Detection Using Voting Spaces Trained by Few Samples, Optical Engineering, 52 (9), 093105 (September 16, 2013)
[23]Lishen Pei, Mao Ye*, Pei Xu, Xuezhuan Zhao, Tao Li, Multi-Class Action Recognition based on Inverted Index of Action States. ICIP 2013.
[24]Haiyang Wang, Mao Ye * and Shangming Yang, Shadow Compensation and Illumination Normalization of Face Image, Machine Vision and Applications, Volume 24, Issue 6 (2013), Page 1121-1131
[25]Tao Li, Mao Ye *, Feng Pang, Haiyang Wang and Jian Ding, An Efficient Fire Detection Method Based on Orientation Feature. International Journal of Control, Automation, and Systems, vol. 11, no. 5, pp.1038-1045, 2013
[26]Songan Mao, Mao Ye*, Xue Li, Feng Pang, Jinglei Zhou, Rapid Vehicle Logo Region Detection Based on Information Theory, Computers and Electronic Engineering，Vol, Issue 3, April 2013, Pages 863–872
[27]Jinglei Zhou, Mao Ye*, etc，Clothing-to-Words Mapping Using Word Separation Method, Computers and Electronic Engineering，Vol 39, No 2, Feb 2013, pp: 361–372
[28]Jianbin Gao,Jianping Li, Qi Xia, and Mao Ye*, Improved SOFI Algorithm for Blind Extraction of Smooth Signals, COMPEL, Vol 32, No 2, 597–605,2013
[29] Jinglei Zhou, Mao Ye*, etc, Rapid and Robust Traffic Accident Detection Based on Orientation Map, Optical Engineering, Vol. 51, No. 11, pp. 117201, 2012
[30] Bo Wang, Mao Ye*, Xue Li, Fengjuan Zhao, Jian Ding, Abnormal Crowd Behavior Detection using High Frequency and Spatio Temporal Features, Machine Vision and Applications. Vol 9, No 5, 905-912,2012
[31]Ren Dongxiao，Ye Mao*，Extracting Post-Nonlinear Signal with Specific Kurtosis Range，Applied Mathematics and Computation，Vol.218, No 9, 5726–5738,2012
[32]Bo Wang, Mao Ye*, Xue Li and Fengjuan Zhao, Abnormal Crowd Behavior Detection using Size-Adapted Spatio-Temporal Features. International Journal of Control, Automation, and Systems, 9(5):905-912,2011
[33]Liqiang Wang*, Mao Ye*, Jian Ding, Yuanxiang Zhu, Hybrid Fire Detection Using Hidden Markov Model and Luminance Map, Computers and Electronic Engineering. Vol.37，No 6，905-915. 2011
[34]Ren Dongxiao*, Ye Mao*，Extracting Post-Nonlinear Signal with reference, Computers and Electronic Engineering. Vol 37，No 6，1171-1181，2011
[35]Jianbin Gao, Mao Ye*，etc，A Globally Convergent MCA Algorithm by Generalized Eigen-Decomposition，International Journal of Computational Intelligence Systems (IJCIS), Vol. 4, No 5, 991-1001，2011
[36]Mao Ye*, Xue Li, Maria E. Orlowska, Projected Outlier Detection in High Dimensional Data Set with Mixed Attributes, Expert system with Applications. 36 , pp. 7104-7113. 2009
[37]Gao Zengan*, Mao Ye*, A framework for Data Mining-Based Anti-Money Laundering Research, Journal of Money Laundering Control, Vol. 10, No.2, 2007.
[38]Mao Ye*, Xue Li, An Efficient Measure of Signal Temporal Predictability for Blind Signal Separation, Neural Processing Letters. Vol.26, No.1, pp. 57-68. 2007
[39]Mao Ye*, Xu-Qian Fan, Xue Li, A class of self-stabilizing MCA Learning Algorithms, IEEE Trans. Neural Networks, Vol 17. No.6,，pp. 1634-1638. 2006
[40]Mao Ye*, Global convergence analysis of a‘Non-negative ICA’algorithm, IEEE Trans. Neural Networks. Vol. 17, No. 1, pp.523-526. JANUARY. 2006
[41]Mao Ye*, Global convergence analysis of a self-stabilized MCA learning algorithm, Neurocomputing. Vol. 67C pp 321-327. 2005
[42]Mao Ye*, Zhang Yi, Complete Convergence of Competitive Neural Networks with Different Time Scales , Neural processing letters. Vol. 21, No. 1, pp. 53 - 60. 2005
[43]Mao Ye*, Zhang Yi, Jianchen Lv, A globally convergent PCA learning algorithm, Neural Computing and Applications. Vol. 14, No. 1, pp. 18-24. 2005
[44]Mao Ye*, Existence and asymptotic stability of relaxation discrete shock profiles, Mathematics of Computation, Vol.73, pp.1261-1296. 2004
[45]Mao Ye*, Numerical boundary layers of conservation laws with relaxation extension, Applied Numerical Mathematics, Vol. 51(2-3), pp. 385-405. 2004.
教學工作
本科生課程：
[1]2013-2014,秋季,資料庫系統原理
[2] 2014-2016,秋季,學術規範與論文寫作
其他信息
計算機學會計算機視覺專委會,多媒體計算專委會委員。中科院專業領域2區期刊Engineering Applications of Artificial Intelligence編委(AE)
