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个人信息:Personal Information
教授
性别:女
毕业院校:西安交通大学
在职信息:在岗
所在单位:人工智能学院
学科:计算机科学与技术
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个人简介:Personal Profile
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、多模态学习等。目前,刘芳教授的谷歌学术引用量为35000+、H指数为85、i10指数为580+,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、TCSVT、TMM、IF、TGRS、PR、CVPR、AAAI、IJCAI、ECCV、ACMMM等)发表论文数十篇,以第一完成人获国家发明专利100余项,获省部级一等奖励以上成果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,所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科研项目,同时承担和完成了包括“863”、国家自然科学基金和国防重大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、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。
刘芳教授合作出版了《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》在内的专著十余部。
个人主页(推荐):http://web.xidian.edu.cn/fliu/
谷歌学术主页:https://scholar.google.com/citations?user=qrQkfxYAAAAJ
DBLP学术主页:https://dblp.org/pid/67/5807-1.html
近期研究方向:
[1] 大数据感知与模式识别
[2] 机器学习与智能图像处理
[3] 多模态学习与因果推理
近期发表论文(*为通讯作者):
[42] Fang Liu*, Jiahao Wang, Licheng Jiao, Jie Zhang, Hao Wang, Shuo Li, Lingling Li, Puhua Chen, Xu Liu, Wenping Ma, Shuang Wang, Shuyuan Yang, Xiangrong Zhang, Yaoyang Du, Qianyue Bao, Long Sun, Biao Hou. Remote Sensing Video Tracking: Current Status, Challenges and Future. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025. https://doi.org/10.1109/JSTARS.2025.3573572. NEW!
[41] Hao Wang, Fang Liu*, Licheng Jiao, Jiahao Wang, Shuo Li, Lingling Li, Puhua Chen, Xu Liu, Wenping Ma. VLPA-CLIP: Video Language Prompting and Adapting CLIP for efficient video action recognition[J]. Pattern Recognition, 2025, https://doi.org/10.1016/j.patcog.2025.111770. NEW!
[40] Jiahao Wang, Fang Liu*, Licheng Jiao, Hao Wang, Shuo Li, Lingling Li, Puhua Chen, Xu Liu, Wenping Ma. Change Knowledge-Guided Vision-Language Remote Sensing Change Detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 2025. https://doi.org/10.1109/TGRS.2025.3568521. NEW!
[39] Shuo Li, Fang Liu*, Zehua Hao, Xinyi Wang, Lingling Li, Xu Liu, Puhua Chen, Wenping Ma. Logits DeConfusion with CLIP for Few-Shot Learning[C]. Computer Vision and Pattern Recognition (CVPR), 2025. NEW!
[38] Yang Liu, Fang Liu*, Licheng Jiao, Qianyue Bao, Shuo Li, Lingling Li, Xu Liu. Knowledge-Driven Compositional action recognition[J]. Pattern Recognition, https://doi.org/10.1016/j.patcog.2025.111452, 2025. NEW!
[37] Pengfang Li, Fang Liu*, Licheng Jiao, Shuo Li, Xu Liu, Puhua Chen, Lingling Li, Zehua Hao. LLM Knowledge-Driven Target Prototype Learning for Few-Shot Segmentation[J]. Knowledge-Based Systems, https://doi.org/10.1016/j.knosys.2025.113149, 2025. NEW!
[36] Shuo Li, Fang Liu*, Licheng Jiao, Lingling Li, Puhua Chen, Xu Liu, Wenping Ma. Prompt-Based Concept Learning for Few-Shot Class-Incremental Learning[J]. IEEE Transactions on Circuits and Systems for Video Technology, https://doi.org/10.1109/TCSVT.2025.3525545, 2025. NEW!
[35] Zehua Hao, Fang Liu*, Licheng Jiao, Yaoyang Du, Shuo Li, Hao Wang, Pengfang Li, Xu Liu, Puhua Chen. Preserving text space integrity for robust compositional zero-shot learning via mixture of pretrained experts[J]. Neurocomputing, https://doi.org/10.1016/j.neucom.2024.128773, 2025. NEW!
[34] Yaoyang Du, Fang Liu*, Licheng Jiao, Shuo Li, Zehua Hao, Pengfang Li, Jiahao Wang, Hao Wang, Xu Liu. Text generation and multi-modal knowledge transfer for few-shot object detection[J]. Pattern Recognition, https://doi.org/10.1016/j.patcog.2024.111283, 2024.
[33] 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, https://doi.org/10.1109/TCSVT.2024.3436878, 2024.
[32] 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, https://doi.org/10.1016/j.inffus.2024.102531, 2024.
[31] 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, https://doi.org/10.1109/TGRS.2024.3417965, 2024.
[30] 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.
[29] 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.
[28] 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.
[27] 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.
[26] 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.
[25] Shuo Li, Fang Liu*, Licheng Jiao, Puhua Chen, Lingling Li. Self-supervised self-organizing clustering network: A novel unsupervised representation learning method[J]. IEEE Transactions on Neural Networks and Learning Systems, vol.35, no.2, pp. 1857-1871, Feb. 2024.
[24] 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.
[23] 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.
[22] Pengfang Li, Fang Liu*, Licheng Jiao, Shuo Li, Lingling Li, Xu Liu and Xinyan Huang. Knowledge Transduction for Cross-Domain Few-Shot Learning[J]. Pattern Recognition, 2023.
[21] 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.
[20] 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.
[19] 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.
[18] 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.
[17] 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.
[16] 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.
[15] 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, 126433, 2023.
[14] 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.
[13] 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.
[12] Shuo Li, Fang Liu*, Licheng Jiao, Puhua Chen, Xu Liu and Lingling 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.
[11] 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.
[10] 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.
[9] 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.
[8] 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.
[7] 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, 14, 2451, 2022.
[6] 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[J]. 计算机学报,Vol.45, No.12, pp:2561-2575, 2022.
[5] 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.
[4] 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.
[3] 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.
[2] 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.
[1] 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.
更多论文请访问:
(1)谷歌学术主页:https://scholar.google.com/citations?user=qrQkfxYAAAAJ
(2)DBLP学术主页:https://dblp.org/pid/67/5807-1.html
近期申请和授权的专利:
[1] 一种基于线流的视频运动稀疏化表征方法,刘芳;李玲玲;李硕;焦李成;陈璞花;马文萍;鲍骞月;刘旭,申请号:202310467461.9,申请时间:2023年04月26日.
[2] 一种人脸检测质量评分方法及系统,刘芳;任保家;黄欣研;李玲玲;刘洋;刘旭;郭雨薇;郝泽华,专利号:ZL202110688239.2,专利申请日:2021年06月21日.
[3] 基于3D卷积和多级语义信息融合的行为识别方法及系统,刘芳;唐瑜;李玲玲;杨苗苗;李鹏芳;李硕;郭雨薇;黄欣研,专利号:ZL202110657341.6,专利申请日:2021年06月11日.
[4] 一种基于边Transformer图神经网络的小样本图像分类方法及系统,刘芳;张瀚;马文萍;李玲玲;李鹏芳;杨苗苗;刘洋;刘旭,专利号:ZL202110657352.4,专利申请日:2021年06月11日.
[5] 一种基于语义感知图神经网络的小样本图像分类方法及系统,刘芳;马文萍;张瀚;李玲玲;刘旭;陈璞花;郭雨薇;李鹏芳,专利号:ZL202110656523.1,申请时间:2021年06月11日.
[6] 一种多特征融合的孪生网络目标跟踪方法及系统,刘芳;焦李成;张松玲;李玲玲;刘旭;陈璞华;古晶;郭雨薇,专利号:ZL202110603006.8,专利申请日:2021年05月31日.
[7] 基于两阶段掩码指导的生成对抗网络人脸校正方法及系统,刘芳;李任鹏;李玲玲;焦李成;黄欣研;刘旭;陈璞华;李硕,专利号:ZL202110603035.4,专利申请日:2021年05月31日.
[8] 基于K-组合均值特征增强的小样本目标检测方法及系统,刘芳;焦李成;刘静;刘旭;李鹏芳;李玲玲;郭雨薇;古晶,专利号:ZL202110605372.7,专利申请日:2021年05月31日.
[9] 一种基于身份约束的生成对抗网络人脸校正方法及系统,刘芳;李玲玲;李任鹏;焦李成;刘旭;黄欣研;陈璞华;鲍骞月,申请号:202110605400.5,申请时间:2021年05月31日.
[10] 基于空间位置特征重加权的小样本目标检测方法及系统,刘芳;焦李成;熊怡梦;刘旭;李鹏芳;李玲玲;郭雨薇;陈璞花,申请号:202110605399.6,申请时间:2021年05月31日.
[11] 一种基于语义特征和度量学习的小样本目标检测方法及系统,刘芳;刘静;焦李成;李玲玲;刘旭;李鹏芳;郭雨薇;陈璞花,申请号:202110603017.6,申请时间:2021年05月31日.
[12] 基于关键帧序列和行为信息的两阶段行为识别方法及系统,刘芳;李玲玲;唐瑜;焦李成;陈璞华;郭雨薇;刘旭;古晶,申请号:202110605394.3,申请时间:2021年05月31日.
[13] 基于动作知识库与集成学习的视频行为识别方法及系统,刘芳;李玲玲;王宇航;杨苗苗;黄欣研;刘旭;郭雨薇;陈璞花,申请号:202110618201.8,申请时间:2021年05月31日.
[14] 一种基于素描信息的光学遥感图像舰船轮廓提取方法,陈璞花;江立;刘芳;焦李成;孙杰;古晶,申请号:201910512627.8,申请日:2019年06月13日,授权号:ZL201910512627.8.
[15] 一种基于信息交互和迁移学习的SAR图像飞机目标检测方法,刘芳;焦李成;王莹;李玲玲;郭雨薇;侯彪;陈璞花;马文萍;杨淑媛,申请号:201910485819.4,授权号:ZL201910485819.4.
[16] 一种基于素描图候选框策略和Fast R-CNN的飞机目标检测方法,刘芳;李玲玲;闫俊起;焦李成;陈璞华;郭雨薇;马文萍;杨淑媛;侯彪,申请号:201910485808.6,授权号:ZL201910485808.6.
[17] 基于几何结构双路卷积网络的光学遥感图像目标检测方法,刘芳;李玲玲;王哲;焦李成;陈璞花;郭雨薇;马文萍;张丹,申请号:201910460842.8,授权号:ZL201910460842.8.
[18] 基于素描信息和超像素分割的光学遥感图像海陆分割方法,陈璞花;江立;刘芳;焦李成;古晶;刘红英;郭雨薇,申请号:201910375910.0,授权号:ZL201910375910.0.
[19] 一种基于素描标注信息的生成对抗迁移学习方法,刘芳;焦李成;习亚男;郭雨薇;李玲玲;侯彪;陈璞花;马文萍;杨淑媛,申请号:201910401740.9,申请时间:2019年05月15日.
[20] 一种基于轮廓结构学习模型的SAR图像语义分割方法,刘芳;张雅科;焦李成;郭雨薇;李玲玲;侯彪;杨淑媛;陈璞花;古晶,申请号:201811184691.X,授权号:ZL201811184691.X.
[21] 基于素描图和先验约束的高分辨SAR图像路网检测方法,刘芳;李玲玲;王雅静;焦李成;郭雨薇;古晶;陈璞花;马文萍;马晶晶,申请号:201810697379.4,授权号:ZL201810697379.4.
[22] 基于素描表示和结构化聚类的非凸压缩感知优化重构方法,刘芳;李婉;李婷婷;陈璞花;郝红侠;焦李成;马文萍;古晶,申请号:201710707916.4,授权号:ZL201710707916.4.
[23] 一种基于G0分布的随机梯度变分贝叶斯SAR图像分割方法,刘芳;孙宗豪;焦李成;李婷婷;郝红侠;古晶;马文萍;陈璞花,申请号:201710702367.1,授权号:ZL201710702367.1.
[24] 基于素描线段拓扑结构的SAR图像目标检测方法,刘芳;李婷婷;闫晓莉;郝红侠;焦李成;尚荣华;马文萍;马晶晶;杨淑媛,申请号:201510938357.9,授权号:ZL201510938357.9.