叶茂
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教授
研究领域：机器学习与计算机视觉
办公室＆实验室：：
电子邮件：maoye@uestc.edu.cn
联系电话：
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教育背景
1991.9-1995.7 四川师范大学 学士 1995.9-1998.6 电子科技大学 硕士 1999.9-2002.7 香港中文大学 博士
社会工作
Engineering Applications of Artificial Intelligence编委 中兴通讯技术编委
奖励情况
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,作为主研获得2018年中国图形图像学学会科学技术二等奖，2019年四川省科技进步奖1等奖。
主持项目（近5年）
基于人工智能的视频编码系统及应用验证项目 2019.8-2023.8 科技部国家重点研发计划 多源涉诉信访智能处置技术研究子课题 2018.12-2021.12 科技部国家重点研发计划 基于特征学习的领域自适应目标检测方法研究 2014.1-2017.12 国家自然科学基金委 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 国家自然科学基金委 基于人工智能视觉中台研究 2020.7-2023.7 四川省重点研发计划 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 四川省科技厅 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 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 成都市科技局
学术成果 （代表性研究成果，部分论文开源代码 https://github.com/maouestc）
Lin Xiong, Mao Ye, Dan Zhang,Yan Gan, Yiguang Liu, Source data-free domain adaptation for a faster R-CNN, Pattern Recognition, 108436, 2022 Dan Zhang, Mao Ye, YiguangLiu, Lin Xiong, Lihua Zhou, Multi-source unsupervised domain adaptation for object detection, Information Fusion, Volume 78, February 2022, Pages 138-148 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 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 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 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 Y Zhang, M Ye, Y Gan, W Zhang, Knowledge based domain adaptation for semantic segmentation, Knowledge-Based Systems 193, 105444, 2020 F Zhang, X Zhu, H Dai, M Ye, C Zhu, Distribution-aware coordinate representation for human pose estimation, CVPR2020 Feng Zhang, Xiatian Zhu, Mao Ye, Fast Human Pose Estimation, CVPR2019 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 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 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 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. Song Tang, Mao Ye, Pei Xu, Xudong Li, Adaptive pedestrian detection by predicting classifier, Neural Comput & Applic (2019) 31:1189–1200 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 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 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 Xudong Li, Mao Ye*, Dan Liu, Feng Zhang, Song Tang, Memory-based Object Detection in Surveillance Scenes, ICME2016. 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) 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 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) 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 Pei Xu, Mao Ye, etc, Dynamic Background Learning through Deep Auto-encoder Networks, ACM MM2014 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 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. 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 Ren Dongxiao，Ye Mao，Extracting Post-Nonlinear Signal with Specific Kurtosis Range，Applied Mathematics and Computation，Vol.218, No 9, 5726–5738, 2012 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 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. （SCI）2006 Mao Ye, Global Convergence Analysis of a Discrete Time Nonnegative ICA Algorithm, IEEE Trans. Neural Networks，Vol. 17, No. 1, pp.523-526. JANUARY. SCI）2006 Mao Ye, Existence and asymptotic stability of relaxation discrete shock profiles, Mathematics of Computation, Vol.73, pp.1261-1296. 2004 Mao Ye, Numerical boundary layers of conservation laws with relaxation extension, Applied Numerical Mathematics, Vol. 51(2-3), pp. 385-405. 2004
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