刘芳　二级教授

硕士/博士生导师

博士学科：(081203)计算机应用技术

硕士学科：(081203)计算机应用技术

工作单位：人工智能学院

通信地址：西安电子科技大学224信箱

电子邮箱：f63liu@163.com

办公电话：88204310

办公地点：主楼II区2层228

        刘芳，女，二级教授，博士生导师，享受国务院特殊津贴的专家，国家自然科学奖获得者，建国七十周年奖章获得者，IEEE高级会员，现为西安电子科技大学华山特聘教授和学术带头人，主要研究方向包括大数据感知与模式识别、机器学习与智能图像处理、多模态学习及可解释性等。目前，刘芳教授的谷歌学术引用量为30000+、H指数为79、i10指数为520+，入选2024年全球前2%科学家榜单（全学科职业生涯影响力榜单和全学科单年度影响力榜单）、2023年全球前2%顶尖科学家榜单。在领域内主流期刊和会议上（TNNLS、TIP、TCYB、TMM、TCSVT、IF、TGRS、PR、AAAI、IJCAI、ACMM、ECCV等）发表论文100余篇，以第一完成人获国家发明专利100余项，获省部级一等奖以上10余项，培养的博士和硕士多人入选省级、一级学会优秀论文，数十人获国家相关人才计划支持，指导的学生在领域内主流竞赛（CVPR、ICCV、ECCV、IGRSS等）获得100余项冠亚季军。

        刘芳教授长期致力于人工智能核心算法的研究，所开展的基于自然启发的智能优化算法获得国家自然科学二等奖，这是从人类进化的可解释性角度的典型代表性工作，其中特别是针对高维奇异点的检测和识别难题，这也是模型攻击与安全性研究的核心，从表征、学习、优化等角度提出了系列启发式的有效解决办法。刘芳教授参加了包括“973”、国家自然科学基金重点项目等国家科研项目，同时承担和完成了包括“863”、国家自然科学基金和基础科研基金等二十余项国家科研任务，获2004年陕西省创新能手、获陕西省科学技术进步二等奖（1998年）、国家教育部科技进步二等奖（1999年）、2008年陕西省科学技术一等奖、2009年国家教育部自然科学奖一等奖、2009年陕西省高等学校科学技术奖一等奖、2010年陕西省科学技术奖一等奖、2011年教育部高等学校技术发明奖二等奖、2011年中国电子学会电子信息科学技术奖 二等奖、2012年陕西省科学技术奖一等奖、2017年陕西省科学技术奖一等奖和2013年国家自然科学奖二等奖等多项科技奖励。

        刘芳教授合作出版《免疫优化计算、学习与识别》、《智能数据挖掘与知识发现》、《图像多尺度几何分析理论与应用——后小波分析理论与应用》、《自然计算、机器学习与图像理解前沿》、《智能SAR图像处理与解译》、《高分辨遥感影像学习与识别》、《稀疏学习、分类与识别》、《认知计算与多目标优化》、《量子计算、优化与学习》、《深度学习、优化与识别》、《遥感影像深度学习智能解译与识别》、《模式识别》、《简明人工智能》、《人工智能、类脑计算与图像解译前沿》、《遥感脑理论及应用》和《深度学习的理论基础与核心算法》等专著十余部。

   学术主页：    谷歌学术        DBLP

   近几年部分论文（更多论文）：

• Jiahao Wang, Fang Liu, Licheng Jiao, Yingjia Gao, Hao Wang, Shuo Li, Lingling Li, Puhua Chen, Xu Liu. Visual and Language Collaborative Learning for RGBT Object Tracking[J]. IEEE Transactions on Circuits and Systems for Video Technology, doi: 10.1109/TCSVT.2024.3436878, 2024. NEW!
• Jiahao Wang, Fang Liu, Licheng Jiao, Hao Wang, Shuo Li, Lingling Li, Puhua Chen, Xu Liu. Multi-modal visual tracking based on textual generation[J]. Information Fusion, doi: 10.1016/j.inffus.2024.102531, 2024. NEW!
• Shuo Li, Fang Liu, Licheng Jiao, Xu Liu, Puhua Chen, Lingling Li. Mask-Guided Correlation Learning for Few-Shot Segmentation in Remote Sensing Imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2024.3417965, 2024. NEW!
• Yang Liu, Fang Liu, Licheng Jiao, Qianyue Bao, Long Sun, Shuo Li, Lingling Li, Xu Liu. Multi-grained Gradual Inference Model for Multimedia Event Extraction[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2024. NEW!
• Yang Liu, Fang Liu, Licheng Jiao, Qianyue Bao, Lingling Li, Yuwei Guo, Puhua Chen. A Knowledge-based Hierarchical Causal Inference Network for Video Action Recognition[J]. IEEE Transactions on Multimedia, 2024. NEW!
• Jiahao Wang, Fang Liu, Licheng Jiao, Yingjia Gao, Hao Wang, Lingling Li, Puhua Chen, Xu Liu and Shuo Li. Satellite Video Object Tracking based on Location Prompts[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2024.  NEW!
• Hao Wang, Fang Liu, Licheng Jiao, Jiahao Wang, Zehua Hao, Shuo Li, Lingling Li, Puhua Chen and Xu Liu. ViLT-CLIP: Video and Language Tuning CLIP with Multimodal Prompt Learning and Scenario-guided Optimization [C]. In Proceedings of the AAAI Conference on Artificial Intelligence, 2024.  NEW!
• Fang Liu, Xiaoxue Qian, Licheng Jiao, Xixangrong Zhang, Lingling Li and Yuanhao Cui. Contrastive Learning-Based Dual Dynamic GCN for SAR Image Scene Classification[J]. IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 1, pp. 390-404, Jan. 2024.  NEW!
• Shuo Li, Fang Liu, Licheng Jiao, Xu Liu and Puhua Chen, Learning Salient Feature for Salient Object Detection Without Labels[J]. IEEE Transactions on Cybernetics, vol.53, no.2, pp. 1012-1025, 2023.
• Shuo Li, Fang Liu, Zehua Hao, Licheng Jiao, Xu Liu and Yuwei Guo. MinEnt: Minimum entropy for self-supervised representation learning[J]. Pattern Recognition, vol.138, 109364, 2023.
• Pengfang Li, Fang Liu, Licheng Jiao, Shuo Lia, Lingling Li, Xu Liu and Xinyan Huang. Knowledge Transduction for Cross-Domain Few-Shot Learning[J]. Pattern Recognition, 2023.
• Xiaoxue Qian, Fang Liu, Licheng Jiao, Xiangrong Zhang, Xinyan Huang, Shuo Li, Puhua Chen and Xu Liu. Knowledge transfer evolutionary search for lightweight neural architecture with dynamic inference[J]. Pattern Recognition, vol.143, 109790, 2023.
• 黄欣研, 刘芳, 鲍骞月, 李任鹏, 刘旭, 李玲玲, 陈璞花, 刘洋. 基于多任务学习和身份约束的生成对抗网络人脸校正识别方法[J]. 电子学报, Vol.51, No.10, pp:2936-2949, 2023.
• Xinyan Huang, Fang Liu, Yuanhao Cui, Puhua Chen, Lingling Li, Pengfang Li. Faster and Better: A Lightweight Transformer Network for Remote Sensing Scene Classification[J]. Remote Sensing, 15(14):3645, 2023. 
• Jiahao Wang, Fang Liu, Licheng Jiao, Hao Wang, Hua Yang, Xu Liu, Lingling Li and Puhua Chen. SSCFNet: A Spatial-spectral Cross Fusion Network for Remote Sensing Change Detection[J]. Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023.
• Jiahao Wang, Fang Liu, Hao Wang, Xu Liu, Licheng Jiao, Hua Yang, Lingling Li and Puhua Chen. SDCDNet: A Semi-Dual Change Detection Network Framework with Super-Weak Lable for Remote Sensing Image[J]. IEEE Transactions on Geoscience and Remote Sensing, VOL.61, 5612714, 2023.
• Yake Zhang, Fang Liu, Licheng Jiao, Shuyuan Yang, Lingling Li, Meijuan Yang, Jianlong Wang and Xu Liu. Curvelet Adversarial Augmented Neural Network for SAR Image Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, VOL.61, 4400717, 2023.
• Pengfang Li, Fang Liu, Licheng Jiao, Lingling Li, Puhua Chen and Shuo Li. Task context transformer and GCN for few-shot learning of cross-domain[J]. Neurocomputing, vol.548, 2023, 126433.
• Shuo Li, Fang Liu and Licheng Jiao. Self-Training Multi-Sequence Learning with Transformer for Weakly Supervised Video Anomaly Detection[C]. In Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36(2), pp. 1395-1403, 2022.
• Qianyue Bao, Fang Liu, Yang Liu, Licheng Jiao, Xu Liu and Lingling Li. Hierarchical scene normality-binding modeling for anomaly detection in surveillance videos[C]. In Proceedings of the 30th ACM International Conference on Multimedia, pp. 6103-6112, 2022.
• Shuo Li, Fang Liu, Licheng Jiao, Puhua Chen, Xu Liu and Liling Li. MFNet: A Novel GNN-Based Multi-Level Feature Network With Superpixel Priors[J]. In IEEE Transactions on Image Processing, vol. 31, pp. 7306-7321, 2022.
• Yuanhao Cui, Fang Liu, Licheng Jiao, Yuwei Guo, Xuefeng Liang, Lingling Li, Shuyuan Yang and Xiaoxue Qian.Polarimetric Multipath Convolutional Neural Network for PolSAR Image Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, VOL. 60, 5207118, 2022.
• Xiaoxue Qian, Fang Liu, Licheng Jiao, Xiangrong Zhang, Puhua Chen, Lingling Li, Jing Gu and Yuanhao Cui. A Hybrid Network With Structural Constraints for SAR Image Scene Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, VOL. 60, 5202717, 2022.
• Shuo Li, Fang Liu, Zehua Hao, Kaibo Zhao and Licheng Jiao. Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space[C]. In European Conference on Computer Vision, vol. 13691, pp. 420-436, 2022.
• Yaoyang Du, Fang Liu, Licheng Jiao, Zehua Hao, Shuo Li, Xu Liu, Jing Liu. Augmentative contrastive learning for one-shot object detection[J]. Neurocomputing, 513: 13-24, 2022.
• Yuanhao Cui, Fang Liu, Xu Liu, Lingling Li and Xiaoxue Qian. TCSPANet: Two-Staged Contrastive Learning and Sub-Patch Attention Based Network for PolSAR Image Classification[J]. Remote Sensing, 2022, 14, 2451.
• 李鹏芳, 刘芳, 李玲玲, 刘旭, 冯志玺, 焦李成, 熊怡梦. 嵌入标签语义的元特征再学习和重加权小样本目标检. 计算机学报，Vol.45, No.12, pp:2561-2575, 2022.
• Xiaoxue Qian, Fang Liu, Licheng Jiao, Xiangrong Zhang, Yuwei Guo, Xu Liu and Yuanhao Cui. Ridgelet-Nets With Speckle Reduction Regularization for SAR Image Scene Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, Vol.59, No.11, pp:9290-9306, 2021.
• Yake Zhang, Fang Liu, Licheng Jiao, Shuyuan Yang, Lingling Li and Meijuan Yang. Discriminative Sketch Topic Model With Structural Constraint for SAR Image Classification[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, Vol.13:5730-5745, 2020.
• Fang Liu, Puhua Chen, Yuanjie Li, Licheng Jiao, Dashen Cui, Yuanhao Cui and Jing Gu. Structural feature learning-based unsupervised semantic segmentation of synthetic aperture radar image[J]. Journal of Applied Remote Sensing, 13(1): 014501-014501, 2019.
• Wan Li, Fang Liu, Licheng Jiao and Fei Hu. Video Reconstruction Based on Intrinsic Tensor Sparsity Model[J]. Signal Processing: Image Communication, 72:113-125, 2019.
• Wan Li, Fang Liu, Licheng Jiao and Fei Hu. Multi-Scale Residual Reconstruction Neural Network With Non-Local Constraint[J]. IEEE Access, 7:70910-70918, 2019.

[1] 大数据感知与模式识别

[2] 机器学习与智能图像处理

[3] 多模态学习及可解释性