叶茂，电子科技大学计算机科学与工程学院教授、博士生导师。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100余篇。主持如国家重点研发计划、国家自然科学基金、四川省科技厅等各个国家、省部级课题。 担任中科院2区期刊Engineering Applications of Artificial Intelligence编委，中兴通讯技术编委。作为主研获得四川省科技进步一等奖1项，中国图象图形学学会科学技术奖二等奖1项。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.

【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、基于数字孪生的决策智能等。

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、基于感知的智能装备等问题，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、决策智能方面，基于自然语言处理技术，人机共融智能技术，知识网络、数字孪生、对抗游戏引擎研发决策智能系统。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、重庆二中院等单位广泛应用。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。

欢迎有志科学研究的同学报考攻读硕士学位和博士学位，非常欢迎同学报考非全日制学位！maoye@uestc.edu.cn

【学术成果】（代表性研究成果，部分论文开源代码 https://github.com/maouestc）

66.Li, Songtao; Ye, Mao; Ji, Luping; Tang, Song; Gan, Yan; Zhu, Xiatian, Illumination Distribution-Aware Thermal Pedestrian Detection, IEEE Transactions on Intelligent Transportation Systems 2024

65.S Xiao, Ye, Mao, Q He, S Li, S Tang, X Zhu, Adversarial Experts Model for Black-box Domain Adaptation, ACM Multimedia 2024

64.Y Zhao, Ye, Mao, L Ji, H Guo, C Zhu,Temporal Adaptive Learned Surveillance Video Compression, IEEE Transactions on Broadcasting 2024

63.Liu, J., Cui, J., Ye, Mao, Zhu, X., & Tang, S. (2024). Shooting condition insensitive unmanned aerial vehicle object detection. Expert Systems with Applications, 246, 123221.

62.Chen, L., Ye, Mao, Ji, L., Li, S., & Guo, H. Multi-Reference-Based Cross-Scale Feature Fusion for Compressed Video Super Resolution. IEEE Transactions on Broadcasting.(2024).

61.Wei, L., Ye, Mao, Ji, L., Gan, Y., Li, S., & Li, X.  Multi-Level Alignments for Compressed Video Super-Resolution. IEEE Transactions on Consumer Electronics.(2024).

60.Chen, S., Ji, L., Zhu, S., & Ye, Mao. MICPL: Motion-Inspired Cross-Pattern Learning for Small-Object Detection in Satellite Videos. IEEE Transactions on Neural Networks and Learning Systems.(2024).

59.Zou, Z., Ye, Mao, Li, X., Ji, L., & Zhu, C. Stable Viewport-Based Unsupervised Compressed 360 Video Quality Enhancement. IEEE Transactions on Broadcasting. (2024).

58.Gan, Y., Xiang, T., Ouyang, D., Zhou, M., & Ye, Mao，SPGAN: siamese projection generative adversarial networks. Knowledge-Based Systems, 285, 111353.(2024).

57.Shu, C., Ye, Mao, Guo, H., & Li, X. Spatial-Temporal Adaptive Compressed Screen Content Video Quality Enhancement. IEEE Transactions on Circuits and Systems II: Express Briefs. (2024).

56.Chen, S., Ji, L., Zhu, J., Ye, Mao, & Yao, X. SSTNet: Sliced spatio-temporal network with cross-slice ConvLSTM for moving infrared dim-small target detection. IEEE Transactions on Geoscience and Remote Sensing.(2024).

55.Gan, Y., Yang, C., Ye, Mao, Huang, R., & Ouyang, D. Generative Adversarial Networks with Learnable Auxiliary Module for Image Synthesis. ACM Transactions on Multimedia Computing, Communications and Applications. (2024).

54.Song Tang, Wenxin Su, Mao Ye, Xiatian Zhu; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024, pp. 23711-23720

53.Hu Wang, Mao Ye, Xiatian Zhu, Shuai Li, Xue Li, Ce Zhu, Compressed-SDR to HDR Video Reconstruction, IEEE TPAMI 2024

52.L Zhou, M Ye, X Li, C Zhu, Y Liu, X Li，Disentanglement then reconstruction: Unsupervised domain adaptation by twice distribution alignments，Expert Systems with Applications 237, 121498，2024

51.L Zhou, N Li, M Ye, X Zhu, S Tang，Source-free domain adaptation with Class Prototype Discovery，Pattern recognition 145, 109974，2024

50.S Tang, Y Shi, Z Song, M Ye, C Zhang, J Zhang，Progressive Source-Aware Transformer for Generalized Source-Free Domain Adaptation，IEEE Transactions on Multimedia,2023

49．Song Tang，An Chang，Fabian Zhang，Xiatian Zhu，Mao Ye，Changshui Zhang， Source-free Domain Adaptation via Target Prediction Distribution Searching，International Journal of Computer Vision，2023

48．Lihua Zhou, Mao Ye, Xiatian Zhu, Siying Xiao, Xu-Qian Fan, Ferrante Neri，Homeomorphism Alignment for Unsupervised Domain Adaptation，ICCV2023

47．Y Zhao, D Luo, F Wang, H Gao, M Ye, C Zhu，End-To-End Compression for Surveillance Video With Unsupervised Foreground-Background Separation，IEEE Transactions on Broadcasting 2023

46. Qichen He, Siying Xiao, Mao Ye, Xiatian Zhu, Ferrante Neri, Dongde Hou, Independent Feature Decomposition and Instance Alignment for Unsupervised Domain Adaptation, IJCAI2023

45.L Zhou, S Xiao, Mao Ye, X Zhu, S Li, Adaptive Mutual Learning for Unsupervised Domain Adaptation, IEEE Transactions on Circuits and Systems for Video Technology, 2023

44. Z Zou, Mao Ye, S Li, X Li, F Dufaux,360 Image Saliency Prediction by Embedding Self-Supervised Proxy Task, IEEE Transactions on Broadcasting,2023

43. D Luo, Mao Ye, S Li, C Zhu, X Li, Spatio-Temporal Detail Information Retrieval for Compressed Video Quality Enhancement, IEEE Transactions on Multimedia,2022

42. Y Gan, T Xiang, H Liu, Mao Ye, Learning-aware feature denoising discriminator, Information Fusion 89, 143-154,2023

41. Zhenbin Wang, Mao Ye, Xiatian Zhu, Liuhan Peng, Liang Tian, Yingying Zhu，MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification, NeurIPS 2022.

40. Peng, Liuhan; Hamdulla, Askar; Ye, Mao; Li, Shuai; Wang, Zhenbin; Li, Xue，OVQE: Omniscient Network for Compressed Video Quality Enhancement,  IEEE Transactions on Broadcasting，2022

39. Lihua Zhou, Mao Ye, Xiatian Zhu, Shuaifeng Li, Yiguang Liu，Class Discriminative Adversarial Learning for Unsupervised Domain Adaptation，ACM Multimedia 2022

38.Han Gao, JINZHONG CUI, Mao Ye, Shuai Li, Yu Zhao, Xiatian Zhu, Structure-Preserving Motion Estimation for Learned Video Compression, ACM Multimedia 2022

37.Shuai Li, KaiXin Wang, Yanbo Gao, Xun Cai, Mao Ye, Geometric warping error aware CNN for DIBR oriented view synthesis, ACM Multimedia 2022

36.Song Tang, Yan Zou, Zihao Song, Jianzhi Lyu, Lijuan Chen, Mao Ye, Shouming Zhong, Jianwei Zhang, Semantic Consistency Learning on Manifold for Source Data-free Unsupervised Domain Adaptation, Neural Networks, 2022

35.Zhiqi Yu, Mao Ye, Siying Xiao, Liang Tian，Learning Missing Instances in Latent Space for Incomplete Multi-view Clustering，Knowledge-based Systems, 2022.

34. Hu Wang, Mao Ye, Xiatian Zhu, Shuai Li, Ce Zhu and Xue Li，KUNet: Imaging Knowledge-Inspired Single HDR Image Reconstruction，IJCAI2022-Long Oral paper,  2022 (3.75%).

33. Shuaifeng Li, Mao Ye, Xiatian Zhu, Lihua Zhou, Lin Xiong, Source-Free Object Detection by Learning to Overlook Domain Style, CVPR2022-Oral paper, 2022.

32.Lin Xiong, Mao Ye, Dan Zhang,Yan Gan, Yiguang Liu, Source data-free domain adaptation for a faster R-CNN, Pattern Recognition, 108436, 2022

31.Zhang Dan, Ye Mao, YiguangLiu, Xiong Lin, Zhou Lihua, Multi-source unsupervised domain adaptation for object detection, Information Fusion, Volume 78, February 2022, Pages 138-148

30.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

29.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

28.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

27.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

26.Y Zhang, M Ye, Y Gan, W Zhang, Knowledge based domain adaptation for semantic segmentation, Knowledge-Based Systems 193, 105444, 2020

25．F Zhang, X Zhu, H Dai, M Ye, C Zhu, Distribution-aware coordinate representation for human pose estimation, CVPR2020

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

23．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

22．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

21．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

20．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.

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

18．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

17．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

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

14．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)

13．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

12．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)

11．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

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

9．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

8．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.

7．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

6．Ren Dongxiao，Ye Mao，Extracting Post-Nonlinear Signal with Specific Kurtosis Range，Applied Mathematics and Computation，Vol.218, No 9, 5726–5738, 2012

5．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

4．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

3．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

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

【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

主持项目(近5年)

1991.9 -- 1995.7
四川师范大学       基础数学       大学本科毕业       理学学士学位

1999.7 -- 2002.7
香港中文大学       计算数学       博士研究生毕业       理学博士学位

2002.7 -- 至今

电子科技大学

1998.4 -- 1999.7

信息产业部电子第29研究所      助理工程师