姓名：叶茂 专业技术职务：教授
联系方式：**
邮箱：maoye@uestc.edu.cn
系别：计算机软件与理论系

联系方式 ** 邮箱 maoye@uestc.edu.cn
专业技术职务_详情页 教授

个人背景 1991年-1995年:四川师范大学,本科;
1996年-1998年:电子科技大学,硕士;
1998年-1999年:中电29所,助理工程师；
1999年-2002年：香港中文大学，博士;
2002年-2005年:电子科技大学,讲师;
2005年-2009年:电子科技大学，副教授;
2009年-至今:电子科技大学,教授,博导;
研究方向 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、基于知识的专家系统等。
1、在机器学习与计算机视觉方面，针对目标检测迁移、智能视频编解码、面向公共安全视频监控、医学图像检测如行人检测、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、迁移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、在知识的专家系统方面，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和智能信访识别系统，在西北工业大学财务处、电子科技大学财务处、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。
讲授课程
本科：《学术论文写作》
研究生：《学术规范与论文写作》
研究成果 研究项目：
1.项目名称，国家重点研发计划，基于人工智能的视频编码系统及应用验证项目，2019.8-2023.8，主持；
2.项目名称，国家重点研发计划，多源涉诉信访智能处置技术研究子课题，2018.12-2021.12，主持；
3.国家自然科学基金，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，主持；
4.国家自然科学基金，基于特征学习的领域自适应目标检测方法研究，2014.1-2017.12，主持；
5.国家自然科学基金，盲信号分离若干基本问题的研究，2008.01-2010.12，主持。
论文列表：（代表性研究成果，部分论文开源代码https://github.com/maouestc）
40.Lin Xiong, Mao Ye, Dan Zhang, Yan Gan, Dongde Hou, Domain adaptation of object detector using scissor-like networks, Neurocomputing 453 (2021) 263–271
39.Yan Min, Mao Ye, Liang Tian, Yulin Jian, Ce Zhu, Shangming Yang, Unsupervised FeatureSelection via Multi-step Markov Probability Relationship, Neurocomputing 453 (2021) 241–253
38.Lin Xiong, Mao Ye, Dan Zhang, Yan Gan, Xue Li and Yingying Zhu, Source-data Free Domain Adaptation of Object Detector through Domain Specific Perturbation, International Journal of Intelligent Systems. 2021
37.Lihua Zhou, Mao Ye, Dan Zhang, Ce Zhu, Luping Ji, Prototype Based Multi-Source Domain Adaptation, IEEE Transactions on Neural Networks and Learning Systems, 2021
36.Y Gan, M Ye, D Liu, S Yang, T Xiang, A novel hybrid augmented loss discriminator for text‐to‐image synthesis, International Journal of Intelligent Systems, 2020
35.X Li, D Zhang, M Ye, X Li, Q Dou, Q Lv, Bidirectional generative transductive zero-shot learning, Neural Computing and Applications, 33(10), 5313-5326, 2021
34.Y Huang, Y Gao, Y Gan, M Ye, A new financial data forecasting model using genetic algorithm and long short-term memory network, Neurocomputing,2020．
33.Y Zhang, M Ye, Y Gan, W Zhang, Knowledge based domain adaptation for semantic segmentation, Knowledge-Based Systems 193, 105444, 2020
32．Y Gan, K Liu, M Ye, Y Qian, Sentence guided object color change by adversarial learning, Neurocomputing 377, 113-121, 2020
31．F Zhang, X Zhu, H Dai, M Ye, C Zhu, Distribution-aware coordinate representation for human pose estimation, CVPR2020
30．Y Gan, K Liu, M Ye, Y Zhang, Y Qian, Generative adversarial networks with denoising penalty and sample augmentation, Neural Computing and Applications, 1-11,2019
29．Y Gan, K Liu, M Ye, Y Qian, Generative adversarial networks with augmentation and penalty, Neurocomputing 360, 52-60,2019
28．Feng Zhang, Xiatian Zhu, Mao Ye, Fast Human Pose Estimation, CVPR2019
27．Yan Gan, Junxin Gong, Mao Ye, Yang Qian, Kedi Liu，Unpaired Cross Domain Image Translation with Augmented Auxiliary Domain Information，Neurocomputing 316, 112-123, 2018
26．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/**
25．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
24．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
23．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.
22．Song Tang, Mao Ye, Pei Xu, Xudong Li, Adaptive pedestrian detection by predicting classifier, Neural Comput & Applic (2019) 31:1189–1200
21．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
20．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.**
19．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
18．Xudong Li, Mao Ye*, Dan Liu, Feng Zhang, Song Tang, Memory-based Object Detection in Surveillance Scenes, ICME2016.
17．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)
16．Xiang Zhang,Ce Zhu, Shuai Wang, Yipeng Liu, Mao Ye, A Bayesian Approach for Camouflaged Moving Object Detection, IEEE Transactions on Circuits and Systems for Video Technology, 2015
15．Min Fu, Pei Xu, Xudong Li, Qihe Liu, Mao Ye, Ce Zhu, Fast Crowd Density Estimation with Convolutional Neural Networks, Engineering Applications of Artificial Intelligence, Volume 43, August 2015, Pages 81–88, 2015 (SCI)
14．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)
13．Pei Xu, Mao Ye, etc, Dynamic Background Learning through Deep Auto-encoder Networks, ACM MM2014
12．Fan Li, Mao Ye, Xudong 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
11．Xin Zhao, Xue Li, 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.
10．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, 905-912, 2012
9．Ren Dongxiao，Ye Maos，Extracting Post-Nonlinear Signal with Specific Kurtosis Range，Applied Mathematics and Computation，Vol.218, No 9, 5726–5738, 2012
8．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
7．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
6．Mao Ye, Global Convergence Analysis of a Discrete Time Nonnegative ICA Algorithm, IEEE Trans. Neural Networks，Vol. 17, No. 1, pp.523-526. JANUARY. 2006
5．Mao Ye, Global convergence analysis of a self-stabilized MCA learning algorithm, Neurocomputing. Vol. 67C pp 321-327. 2005
4．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
3．Mao Ye, Zhang Yi, Jianchen Lv, A globally convergent PCA learning algorithm, Neural Computing and Applications. Vol. 14, No. 1, pp. 18-24. 2005
2．Mao Ye, Existence and asymptotic stability of relaxation discrete shock profiles, Mathematics of Computation, Vol.73, pp.1261-1296. 2004
1．Mao Ye, Numerical boundary layers of conservation laws with relaxation extension, Applied Numerical Mathematics, Vol. 51(2-3), pp. 385-405. 2004
研究成果获奖：
2019年获四川省科技进步一等奖；
2018年获中国图形图像学学会科学技术奖二等奖。
社会兼职及荣誉
Engineering Applications of Artificial Intelligence编委，2015-
中国计算机学会智能机器人、计算机视觉、多媒体技术专委会委员