• 其他栏目

    叶茂

    • 教授 博士生导师 硕士生导师
    • 毕业院校 : 香港中文大学
    • 学历 : 博士研究生毕业
    • 学位 : 理学博士学位
    • 所在单位 : 计算机科学与工程学院(网络空间安全学院)
    • 入职时间 : 2002-08-01
    • 学科 : 计算机应用技术

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    个人简介

    叶茂,男,博士,1973年9月出生。2008年破格提升为博士生指导教师,2009年破格晋升为正教授,电子科技大学机器人中心副主任, 中国工程物理研究院客座教授,西华师范大学兼职教授。计算机学会计算机视觉专委会,多媒体计算专委会委员,自动化学会混合智能专委会委员。2002年从香港中文大学获得计算数学哲学博士学位并加入电子科技大学至今。曾于 2005 - 2006,  2010年分别在昆士兰大学和宾夕法利亚大学做访问学者。入选教育部新世纪优秀人才支持计划, 四川省杰出青年学科带头人支持计划。目前主要研究领域为机器学习与计算机视觉,已发表论文国际一流学术论文70余篇。主持如国家自然科学基金、四川省科技厅等各个国家、省部级课题。并主持开发多个取得良好经济效益的工业产品项目;已授权发明专利20余项;担任多个国际顶级学术会议程序委员会成员和分会场主席,如IJCAI, AAAI, ADMA等。担任中科院2区期刊Engineering Applications of Artificial Intelligence编委, 多个国际一流期刊审稿人如IEEE TNNLS, IEEE TC, IEEE TSP等。荣获2012年华为-电子科技大学优秀合作团队,2017ICME国际会议优秀学生论文奖,2018年中国图象图形学会科学技术奖二等奖。


    【研究领域】

    我及所在课题组的主要研究方向包括:机器学习与计算机视觉、机器人定位与导航技术、文本理解与智能咨询系统

    1、在机器学习与计算机视觉方面,针对目标检测迁移、面向公共安全视频监控如行人检测、行人重识别、行为识别、群体异常检测等问题,结合记忆,融入知识,采用深度学习、深度强化学习等理论和技术手段展开了广泛研究,相关学术成果发表于国际一流学术期刊和会议,申请多项发明专利。

    2、在机器人定位与导航技术方面,主要针对智能机器人(含无人机,无人车)自主运行展开理论和系统研究。 针对室外机器人、慢速无人车在非结构化道路上低成本导航的需求研发了一款社区服务机器人,结合GPS、图像等廉价多模态信息精确度在2内;可在夜晚、雨天等环境下自主导航与避障,避障成功率在95%以上,导航正确率98%以上;在非结构化道路上速度最高可达20公里/小时;可远程遥控退出死锁状态;可为自动垃圾清扫车、社区巡逻等室外机器人提供配套。同时正在研发无人机自主飞行巡检系统。相关学术成果发表于国际一流学术期刊和会议,申请多项发明专利。

    3、在文本理解与智能咨询系统方面,基于自然语言处理技术,人机共融智能技术,智能推荐技术所研发的智能咨询服务机器人,在西北工业大学财务处、电子科技大学财务处、同济大学、四川省图书馆等单位广泛应用。相关学术成果发表于国际一流学术期刊和会议,申请多项发明专利。



    【学术成果】(代表性研究成果)

    1.       Feng Zhang, Xiatian Zhu, Mao Ye*, Fast Human Pose Estimation, CVPR2019

    2.       Feng Zhang, Xiatian Zhu, Mao Ye*, Efficient Human Pose Estimation in Hierarchical Context,Vol 7(1), 29365-29373, IEEE Access, Dec 2019

    3.       Lan LinHuan Luo, Renjie Huang, Mao Ye*, Recurrent Models of Visual Co-Attention for Person Re-Identification, IEEE ACCESS 2019, January 1, 2019

    4.       Y Gan, J Gong, M Ye*, Y Qian, K Liu, S ZhangGANs with Multiple Constraints for Image TranslationComplexity 2018, 4613935, 9 December 2018

    5.       Yan Gan, Junxin Gong, Mao Ye*, Yang Qian, Kedi LiuUnpaired Cross Domain Image Translation with Augmented Auxiliary Domain InformationNeurocomputing 316, 112-123, 2018

    6.       Yuxiao Zhang, Haiqiang Chen, Yiran He, Mao Ye*, Xi Cai, Dan Zhang,  Road Segmentation for All-Day Outdoor Robot Navigation,  Neurocomputing 314 (2018) 316–325, Source code:  https://github.com/yuxiaoz/SGSN;Chinese blog:

                       https://blog.csdn.net/jiongnima/article/details/80880621

    7.       S Du, Y Liu*, M Ye, Z Xu, J Li, J Liu, Single image deraining via decorrelating the rain streaks and background scene in gradient domain, Pattern Recognition 79, 303-317, 2018

    8.       Song TANG, Lijuan CHEN, Jinpeng MI, Mao YE*, Jianwei ZHANG and Qingdu LI, Adaptive Pedestrian Detection by Modulating Features, ROBIO2017.

    9.       Lan Lin, Renjie Huang, Xudong Li, Feng Zhang, and Mao Ye*, Person Re-Identification by Optimally Organizing Multiple Similarity Measures, IEEE Access 5, 26034-26045, 2017

    10.   Xudong Li, Mao Ye*, Yiguang Liu,Ce Zhu, Adaptive deep convolutional neural networks for scene-specific object detection. IEEE Transactions on Circuits and Systems for Video Technology, 2017 , accepted

    11.   Xudong Li, Mao Ye*, Yiguang Liu,Ce Zhu, Memory-based Pedestrian Detection Through Sequence Learning, Multimedia and Expo (ICME), 2017 IEEE International Conference on, 1129-1134, Best Student Paper, Finalist of the World’s FIRST 10K Best Paper Award.

    12.   Song Tang, Mao Ye, Pei Xu, Xudong Li, Adaptive pedestrian detection by predicting classifier, Neural Comput & Applic (2019) 31:1189–1200

    13.   Song Tang, Mao Ye*, Ce Zhu, Yiguang Liu, "Adaptive pedestrian detection using convolutional neural network with dynamically adjusted classifier," J. Electron. Imaging 26(1), 013012 (2017), doi: 10.1117/1.JEI.26.1.013012.

    14.   Xudong Li, Mao Ye*, Yiguang Liu, Dan Liu, Feng Zhang, Song Tang, Accurate object detection using memory-based models in surveillance scenes, Pattern Recognition, Vol 67, July 2017, Pages 73–84

    15.   Pengfei Wu,Yiguang Liu*, Mao Ye ,Yunan Zheng, Geometry Guided Multi-Scale Depth Map Fusion via Graph Optimization, IEEE Transactions on Image Processing, VOL. 26, NO. 3, 1315 - 1329 , MARCH 2017, DOI: 10.1109/TIP.2017.2651383

    16.   Chenfei Xu, Qihe Liu, Mao Ye*, Age invariant face recognition and retrieval by coupled auto-encoder, Neuocomputing, Volume 222, 26 January 2017, Pages 62–71

    17.   Xudong Li, Mao Ye*, Dan Liu, Feng Zhang, Song Tang, Memory-based Object Detection in Surveillance Scenes, ICME2016.

    18.   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 25(3), 033006, 2016(SCI)

    19.   Chenxue Yang, Mao Ye*, Song Tang, Zijian Liu, Tao Xiang, Semi-supervised low-rank representation for image classification, Signal, Image and Video Processing, (2017) 11:73–80 (SCI)

    20.   Lishen Pei, Mao Ye S *  , Xuezhuan Zhao, Yumin Dou and Jiao Bao, Action recognition by learning  temporal slowness invariant features, The Visual Computer, 32:1395–1404,2016 (SCI)

    21.   Yumin Dou, Pei Xu, Mao Ye S* , Xue Li,  Lishen Pei,  Xudong Li, Real-time Multi-class Object Detection Using Two Dimensional Index, Journal of Real-Time Image Processing, 2015 Accept (SCI)

    22.   Qian Zhao, Shuzhi Sam Ge S *, Mao Ye, Sibang Liu, Wei He, Learning Saliency Features for Face Detection and Recognition using Multi-Task Network, International Journal of Social Robotics, November 2016, Volume 8, Issue 5, pp 709–720 (SCI)

    23.   Pengfei Wu, Yiguang Liu*, Mao Ye, etc, Fast and Adaptive 3D Reconstruction with Extensively High Completeness, IEEE Transactions on Multimedia, Volume: 19, Issue: 2, Page(s): 266 – 278, FEB 2017(SCI)

    24.   Xiang Zhang,Ce ZhuS*, Shuai Wang, Yipeng Liu, Mao Ye, A Bayesian Approach for Camouflaged Moving Object Detection, IEEE Transactions on Circuits and Systems for Video Technology, 2015 Accept (SCI)

    25.   Xiang Tao, Tao Li, Mao Ye S* , and Xudong LiDiscriminative boosted forest with convolutional neural network-based patch descriptor for object detection, J. Electron. Imaging 25(1), 013002 (2016).

    26.   Tao Xiang, Tao Li, Mao Ye S * and Zijian Liu, Random Forest with Adaptive Local Template for Pedestrian Detection, Mathematical Problems in Engineering, 767423, 2015

    27.   Min Fu, Pei Xu, Xudong Li, Qihe Liu, Mao Ye S * , Ce Zhu, Fast Crowd Density Estimation with     Convolutional Neural Networks,  Engineering Applications of Artificial Intelligence, Volume 43, August 2015, Pages 81–88, 2015 (SCI)

    28.   Lishen Pei, Mao Ye S *, 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(SCI)

    29.   Xudong Li, Mao Ye S *, 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 (SCI)

    30.   Renjie Huang,  Mao Ye S *, 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 (SCI)

    31.   Shangming Yang, Zhang Yi*, Mao Ye, Xiaofei He, Convergence Analysis of Graph Regularized Non-negative Matrix Factorization, IEEE Transactions on Knowledge and Data Engineering, 2015(SCI)

    32.   Qihe Liu*, Xiaonan Hu, Mao Ye, Xianqiong Cheng and Fan Li, Gas Recognition under Sensor Drift by Using Deep Learning, International Journal of Intelligent Systems, Volume 30, Issue 8, pages 907–922, August 2015 (SCI)

    33.   Pei Xu, Mao Ye S *, etc, Dynamic Background Learning through Deep Auto-encoder Networks, ACM MM2014

    34.   Pei Xu, Mao Ye S *, etc, Motion detection via a couple of autoencoder networks. ICME2014

    35.   Renjie Huang, Tao Li, Mao YeS* 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(SCI)

    36.   Lishen Pei,  Mao Ye S *, 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, 2016 (SCI)

    37.   Chenxue Yang, Tao Li, Mao Ye S *, 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 (SCI)

    38.   Chenxue Yang, Mao Ye S*, Xudong Li, Zijian Liu, Tao Li, Robust Low Rank Image Representations by Deep Matrix Decompositions, Electronics Letters, 50(24):1843-1845, 2014 (SCI)

    39.   Lishen Pei, Mao Ye S, Pei Xu, Xuezhuan Zhao, Guanjun Ge, One Example Based Action Detection In Hough Space. Multimedia Tools and Applications, 72(2): 1751-1772 (2014) (SCI)

    40.   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 (SCI)

    41.   Fan Li*, Mao YeXudong Chen, An extension to Rough c-means clustering based on decision-theoretic Rough Sets model,  International Journal of approximate Reasoning, Vol 55, Issue 1, Part 2, Pages 116-129 (SCI)2014

    42.   Xin Zhao, Xue Li S*, Chaoyi Pang, Quan Z. Sheng, Sen Wang and Mao Ye,, Structured Streaming Skeleton – a New Feature for Online Human Gesture Recognition, ACM Transactions on Multimedia Computing, Communications and Applications,2014, 11 Supp. 1s: 22:1-22:18.

    43.   Chenxue Yang*, Mao Ye S and Zijian Liu, An impulsive periodic single-species Logistic system with diffusion, Journal of Applied Mathematics. Vol.2013,101238,2013

    44.   Pei Xu, Mao Ye* S , Xue Li, Lishen Pei and Pengwei Jiao, Object Detection Using Voting Spaces Trained by Few Samples, Optical Engineering, 52 (9), 093105 (September 16, 2013)

    45.   Lishen Pei, Mao Ye S*, Pei Xu, Xuezhuan Zhao, Tao Li, Multi-Class Action Recognition based on Inverted Index of Action States. ICIP 2013.

    46.   Haiyang Wang, Mao Ye S * and Shangming Yang, Shadow Compensation and Illumination Normalization of Face Image, Machine Vision and Applications, Volume 24, Issue 6 (2013), Page 1121-1131 (SCI)

    47.   Tao Li, Mao Ye S *, 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

    48.    Songan Mao*, Mao Ye S, Xue Li, Feng Pang, Jinglei Zhou, Rapid Vehicle Logo Region Detection Based on Information Theory, Computers and Electronic EngineeringVol, Issue 3, April 2013, Pages 863–872 (SCI)

    49.   Jinglei Zhou, Mao Ye* S, etcClothing-to-Words Mapping Using Word Separation Method, Computers and Electronic EngineeringVol 39, No 2, Feb 2013, pp: 361–372 

    50.   Jianbin Gao,Jianping Li, Qi Xia, and Mao Ye*, Improved SOFI Algorithm for Blind Extraction of Smooth Signals, COMPEL, Vol 32, No 2, 597 – 605SCI2013

    51.   Shangming Yang*, Mao YeGlobal Minima Analysis of Lee and Seung’s NMF Algorithms Neural Processing Letters 38(1): 29-51 (2013)  (SCI)

    52.   Jinglei Zhou, Mao Ye*, etc, Rapid and Robust Traffic Accident Detection Based on Orientation Map,  Optical Engineering, Vol. 51, No. 11, pp. 117201 (SCI) 2012

    53.   Shangming Yang* and Mao Ye, Multistability of alpha-Divergence Based NMF Algorithms, Computers and Mathematics with Applications, Vol. 64, No 2 , 73-88 (SCI) 2012

    54.   Bo Wang*, Mao Yes, 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, 905-912SCI2012

    55.   Ren DongxiaoYe MaosExtracting Post-Nonlinear Signal with Specific Kurtosis RangeApplied Mathematics and ComputationVol.218, No 9, 5726–5738SCI2012

    56.   Bo Wang, Mao Yes*, 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 SCI2011

    57.   Liqiang Wang*, Mao Yes, Jian Ding, Yuanxiang Zhu, Hybrid Fire Detection Using Hidden Markov Model and Luminance Map, Computers and Electronic Engineering. Vol.37 No 6905-915. SCI 2011

    58.   Ren Dongxiao*, Ye MaosExtracting Post-Nonlinear Signal with reference, Computers and Electronic Engineering. Vol 37 No 61171-1181,(SCI2011

    59.   Jianbin Gao, Mao Yes*etcA Globally Convergent MCA Algorithm by Generalized Eigen-DecompositionInternational Journal of Computational Intelligence Systems (IJCIS), Vol. 4, No 5, 991-1001,(SCI2011

    60.   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. SCI2009

    61.   Gao Zengan, Mao Ye*, A framework for Data Mining-Based Anti-Money Laundering Research, Journal of Money Laundering Control, Vol. 10, No.2, 2007.

    62.   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.SCI2007

    63.    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. SCI2006

    64.    Mao Ye*, Global Convergence Analysis of a Discrete Time Nonnegative ICA Algorithm,  IEEE Trans. Neural Networks. Vol. 17, No. 1, pp.523-526. JANUARY. SCI2006

    65.   Zhang Yi*, Mao Ye, J. C. Lv and K. K. Tan, Convergence analysis of a deterministic discrete time system of Oja's PCA learning algorithm, IEEE Trans. Neural Networks. Vol.16, No. 6, pp 1318-1328.SCI2005

    66.   Mao Ye*, Global convergence analysis of a self-stabilized MCA learning algorithm, Neurocomputing. Vol. 67C pp 321-327. SCI2005

    67.   Mao Ye*, Zhang Yi, Complete Convergence of Competitive Neural Networks with Different Time Scales , Neural processing letters. Vol. 21, No. 1, pp. 53 - 60. SCI2005

    68.   Mao Ye*, Zhang Yi, Jianchen Lv, A globally convergent PCA learning algorithm, Neural Computing  and Applications. Vol. 14, No. 1, pp. 18-24. SCI2005

    69.   Mao Ye*, Existence and asymptotic stability of relaxation discrete shock profiles, Mathematics of Computation,  Vol.73, pp.1261-1296. SCI2004

    70.   Mao Ye*, Numerical boundary layers of conservation laws with relaxation extension, Applied Numerical Mathematics, Vol. 51(2-3),  pp. 385-405. SCI2004

    【授权专利】

    1. 朱莺嘤,叶茂,赵欣,基于固有趋势子序列模式分解的出现新的心脏活动趋势的ECG信号获取方法,2011,中国,200810046006.7, 已授权

    2. 朱莺嘤,叶茂,赵欣,郑凯元,基于固有模式子序列模式分解的主机入侵检测方法,2011,中国,200810044516.0, 已授权

    3. 朱莺嘤,叶茂,赵欣,郑凯元,基于固有模式子序列模式分解的网络入侵检测方法,2011,中国,200810044515.6, 已授权

    4. 丁剑,叶茂,王理强,基于视频时间与空间信息的火焰检测方法,2011,中国,201010178309.1, 已授权

    5. 周景磊,叶茂,张旭东,赵欣,王波,磁粉探伤环境下基于复合特征的工件伤痕识别方法,2012,中国,201010162959.7, 已授权

    6. 赵风娟,叶茂,王波,基于群体环境的异常行为检测,2012,中国,201010185895.2, 已授权

    7. 周景磊,叶茂,丁剑,一种基于语义映射的服装图像检索方法,2013, 中国, 201110236889.X, 已授权

    9. 周景磊,叶茂,一种城市交通事故检测方法,2013,中国, 201110358475.4, 已授权

    10. 叶茂, 陈宏毅, 李涛, 李旭冬, 付敏,一种特定姿态实时检测方法, 申请号: 201310414897.8,已授权

    11. 叶茂, 占伟鹏, 徐培, 庞锋, 蔡小路, 谢易道,自适应视频场景的行人检测方法, 申请号: 201310358963.4,已授权

    12. 焦朋伟, 叶茂, 唐红强, 李涛,基于笔画分解的车牌字符识别方法,申请号: 201310245266.8, 已授权

    13.  叶茂, 徐培, 占伟鹏, 黄仁杰, 张之曦, 基于少量样本的快速目标检测方法, 申请号: 201310479987.5, 已授权

    14. 叶茂,苟群森(学),肖华强(学),何文伟(学),申鹏(学), 一种有方向的越界和拌线检测,申请号: 201410243390.5,已授权

    17. 叶茂 李旭冬 李涛 付敏 肖华强 王梦伟, 一种基于卷积神经网络的车辆检测方法, 申请号: 201410299644.5, 已授权

    18. 蔡小路 叶茂 谢易道 赵苗苗 占伟鹏, 一种基于场地标识线轮廓匹配的体育视频分类方法,申请号: 201410323148,9已授权

    19. 李涛,叶茂,李旭东201410339426.X 一种基于级联多级卷积神经网络的人群密度估计方法, 已授权

    22. 叶茂 王梦伟 李旭东 彭明超 苟群森201410393335.4 一种行人检测方法, 已授权

    24. 叶茂 王梦伟 郑梦雅 苟群森 彭明超201410549315.1 基于卷积神经网络的车牌检测方法,已授权

    23. 叶茂 裴利沈 赵雪专 李涛 包姣 窦育民 李旭冬 向涛201410476791.5 一种基于独立子空间网络的行为识别方法,已授权

    25. 苟群森 叶茂 彭明超 王梦伟 申鹏,基于安卓的多特征疲劳实检测, 201510364426.X,已授权

    26. 李旭冬 叶茂 王梦伟 苟群森 李涛 张里静201510466424.1 一种基于卷积神经网络自适应的车辆检测方法,已授权


    项目(5)

     

    项目编号

    起止年月

    排名

    项目来源

    60702071

    盲信号分离若干基本问题的研究

    2008.01-2010.12

    1

    国家自然科学基金委

    61375038

    基于特征学习的领域自适应目标检测方法研究

    2014.1-2017.12

    1

    国家自然科学基金委

    61773093

    面向服务机器人的无监督领域自适应目标检测方法研究

    2018.1-2021.12

    1

    国家自然科学基金委

    NCET-06-0811

    教育部新世纪优秀人才支持计划

    2007.01-2009.12

    1

    教育部

    2018YFC0831800

    多源涉诉信访智能处置技术研究子课题

    2018.12-2021.12

    1

    科技部国家重点研发计划

    17ZDYF3184

    面向图书馆的读者咨询与导读移动智能服务系统开发

    2018.1-2019.12

    1

    四川省科技厅

    09ZQ026-035

    基于视觉异常行为监控若干关键问题研究

    2009.5-2011.12

    1

    四川省科技厅

    2016JY0088

    社会服务机器人行为感知与控制神经计算方法研究

    2016.1-2018.12

    1

    四川省科技厅

    2006J13-065

    数字免疫网络研究

    2006.1-2007.12

    1

    四川省科技厅


    面向低空无人机自主导航系统研发

    2018.12-2020.12

    1

    成都市科技局


    四川省学术与技术带头人培养资金

    2013.7-2015.7

    1

    四川省人事厅

    60903074

    基于元启发式算法的聚类分析关键问题研究

    2010.1-2012.12

    2

    国家自然科学基金委

    2010CB732501

    先验统计模型的建立与非线性优化理论

    20101-2014.12

    4

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